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Recurrent events in survival analysis

Hector Maletta

Is there any way in SPSS 19 to do a survival analysis (Cox Regression) for situations in which more than one event is analyzed? Any other accessible software?

 

This may include one single type of event that may happen several times to a single subject (e.g. getting ill or failing a class at school), or several different kinds of events that may or may not be competing, such as (1) repeating a given class in school after failure the previous year, and  (2) dropping out of school. Dropping out and repeating the class are competing risks; repeating one particular class is not competing with having repeated other classes before or going to repeat another class afterwards.

 

The specific problem I have deals with events that may hinder school progress for children of school age. They may fail to enroll at the normal age, most of which finally enroll albeit at a later age; they may have repeated one or more classes (because they failed to pass it the previous year), or may have dropped out of school.

 

I wish to model the chances of adverse events along the “school history” of a typical child, in terms of the age (or level of education) at which these events may happen.

 

To make things a little more complicated, I do not have in this case a longitudinal study, but a cross section of kids to whom the events have already  happened. The cross section information available is census data for an entire, albeit relatively small [developing] country, so statistical significance in the usual sense is not a problem (tens or hundreds of thousands of kids in each situation). Covariates include household-family variables (SES, education of adults, etc) and characteristics of the child (age, gender,  educational attainment up to the event, child work if any, etc). Some of these covariates might be treated as time-dependent, but this might be (hopefully) avoided.

 

Thanks in advance

 

Hector

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Re: Recurrent events in survival analysis

Ornelas, Fermin-2

You may want to check some nice articles by Singer and Willet. They have researched this area very well.

 

Fermin Ornelas, Ph.D.

 

From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Hector Maletta
Sent: Monday, October 25, 2010 9:28 AM
To: [hidden email]
Subject: Recurrent events in survival analysis

 

Is there any way in SPSS 19 to do a survival analysis (Cox Regression) for situations in which more than one event is analyzed? Any other accessible software?

 

This may include one single type of event that may happen several times to a single subject (e.g. getting ill or failing a class at school), or several different kinds of events that may or may not be competing, such as (1) repeating a given class in school after failure the previous year, and  (2) dropping out of school. Dropping out and repeating the class are competing risks; repeating one particular class is not competing with having repeated other classes before or going to repeat another class afterwards.

 

The specific problem I have deals with events that may hinder school progress for children of school age. They may fail to enroll at the normal age, most of which finally enroll albeit at a later age; they may have repeated one or more classes (because they failed to pass it the previous year), or may have dropped out of school.

 

I wish to model the chances of adverse events along the “school history” of a typical child, in terms of the age (or level of education) at which these events may happen.

 

To make things a little more complicated, I do not have in this case a longitudinal study, but a cross section of kids to whom the events have already  happened. The cross section information available is census data for an entire, albeit relatively small [developing] country, so statistical significance in the usual sense is not a problem (tens or hundreds of thousands of kids in each situation). Covariates include household-family variables (SES, education of adults, etc) and characteristics of the child (age, gender,  educational attainment up to the event, child work if any, etc). Some of these covariates might be treated as time-dependent, but this might be (hopefully) avoided.

 

Thanks in advance

 

Hector



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Re: Recurrent events in survival analysis

Dale Glaser
In reply to this post by Hector Maletta
Hector, though this was with a prior version of SPSS, I had the same question from this listserv on a recurrent events projet I was workin on, and a tthat time R seemed to be the only option..see the following link:
 
and more recent, I belive the frailty package can do recurrent events analysis:
 

Dale Glaser, Ph.D.
Principal--Glaser Consulting
Lecturer/Adjunct Faculty--SDSU/USD/Alliant
Past-President, San Diego Chapter of
American Statistical Association
3115 4th Avenue
San Diego, CA 92103
phone: 619-220-0602
fax: 619-220-0412
email: [hidden email]
website: www.glaserconsult.com

--- On Mon, 10/25/10, Hector Maletta <[hidden email]> wrote:

From: Hector Maletta <[hidden email]>
Subject: Recurrent events in survival analysis
To: [hidden email]
Date: Monday, October 25, 2010, 9:27 AM

Is there any way in SPSS 19 to do a survival analysis (Cox Regression) for situations in which more than one event is analyzed? Any other accessible software?

 

This may include one single type of event that may happen several times to a single subject (e.g. getting ill or failing a class at school), or several different kinds of events that may or may not be competing, such as (1) repeating a given class in school after failure the previous year, and  (2) dropping out of school. Dropping out and repeating the class are competing risks; repeating one particular class is not competing with having repeated other classes before or going to repeat another class afterwards.

 

The specific problem I have deals with events that may hinder school progress for children of school age. They may fail to enroll at the normal age, most of which finally enroll albeit at a later age; they may have repeated one or more classes (because they failed to pass it the previous year), or may have dropped out of school.

 

I wish to model the chances of adverse events along the “school history” of a typical child, in terms of the age (or level of education) at which these events may happen.

 

To make things a little more complicated, I do not have in this case a longitudinal study, but a cross section of kids to whom the events have already  happened. The cross section information available is census data for an entire, albeit relatively small [developing] country, so statistical significance in the usual sense is not a problem (tens or hundreds of thousands of kids in each situation). Covariates include household-family variables (SES, education of adults, etc) and characteristics of the child (age, gender,  educational attainment up to the event, child work if any, etc). Some of these covariates might be treated as time-dependent, but this might be (hopefully) avoided.

 

Thanks in advance

 

Hector

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Re: Recurrent events in survival analysis

Hector Maletta
In reply to this post by Ornelas, Fermin-2

Thanks, Fermin. Will look at those articles. However,  have plenty of references for the matter itself. I was rather looking for software solutions (preferably within SPSS). Dale Glaser has contributed some specific suggestions in that direction.

Hector

 

De: Ornelas, Fermin [mailto:[hidden email]]
Enviado el: Monday, October 25, 2010 3:56 PM
Para: 'Hector Maletta'; [hidden email]
Asunto: RE: Recurrent events in survival analysis

 

You may want to check some nice articles by Singer and Willet. They have researched this area very well.

 

Fermin Ornelas, Ph.D.

 

From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Hector Maletta
Sent: Monday, October 25, 2010 9:28 AM
To: [hidden email]
Subject: Recurrent events in survival analysis

 

Is there any way in SPSS 19 to do a survival analysis (Cox Regression) for situations in which more than one event is analyzed? Any other accessible software?

 

This may include one single type of event that may happen several times to a single subject (e.g. getting ill or failing a class at school), or several different kinds of events that may or may not be competing, such as (1) repeating a given class in school after failure the previous year, and  (2) dropping out of school. Dropping out and repeating the class are competing risks; repeating one particular class is not competing with having repeated other classes before or going to repeat another class afterwards.

 

The specific problem I have deals with events that may hinder school progress for children of school age. They may fail to enroll at the normal age, most of which finally enroll albeit at a later age; they may have repeated one or more classes (because they failed to pass it the previous year), or may have dropped out of school.

 

I wish to model the chances of adverse events along the “school history” of a typical child, in terms of the age (or level of education) at which these events may happen.

 

To make things a little more complicated, I do not have in this case a longitudinal study, but a cross section of kids to whom the events have already  happened. The cross section information available is census data for an entire, albeit relatively small [developing] country, so statistical significance in the usual sense is not a problem (tens or hundreds of thousands of kids in each situation). Covariates include household-family variables (SES, education of adults, etc) and characteristics of the child (age, gender,  educational attainment up to the event, child work if any, etc). Some of these covariates might be treated as time-dependent, but this might be (hopefully) avoided.

 

Thanks in advance

 

Hector

 


NOTICE: This e-mail (and any attachments) may contain PRIVILEGED OR CONFIDENTIAL information and is intended only for the use of the specific individual(s) to whom it is addressed. It may contain information that is privileged and confidential under state and federal law. This information may be used or disclosed only in accordance with law, and you may be subject to penalties under law for improper use or further disclosure of the information in this e-mail and its attachments. If you have received this e-mail in error, please immediately notify the person named above by reply e-mail, and then delete the original e-mail. Thank you.

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Re: Recurrent events in survival analysis

Ornelas, Fermin-2

Hector:

You may want to check their web site for the book Applied Longitudinal Analysis. I think they have both SAS and SPSS coding.

 

Fermin Ornelas, Ph.D.

 

From: Hector Maletta [mailto:[hidden email]]
Sent: Monday, October 25, 2010 12:46 PM
To: Ornelas, Fermin; [hidden email]
Subject: RE: Recurrent events in survival analysis

 

Thanks, Fermin. Will look at those articles. However,  have plenty of references for the matter itself. I was rather looking for software solutions (preferably within SPSS). Dale Glaser has contributed some specific suggestions in that direction.

Hector

 

De: Ornelas, Fermin [mailto:[hidden email]]
Enviado el: Monday, October 25, 2010 3:56 PM
Para: 'Hector Maletta'; [hidden email]
Asunto: RE: Recurrent events in survival analysis

 

You may want to check some nice articles by Singer and Willet. They have researched this area very well.

 

Fermin Ornelas, Ph.D.

 

From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Hector Maletta
Sent: Monday, October 25, 2010 9:28 AM
To: [hidden email]
Subject: Recurrent events in survival analysis

 

Is there any way in SPSS 19 to do a survival analysis (Cox Regression) for situations in which more than one event is analyzed? Any other accessible software?

 

This may include one single type of event that may happen several times to a single subject (e.g. getting ill or failing a class at school), or several different kinds of events that may or may not be competing, such as (1) repeating a given class in school after failure the previous year, and  (2) dropping out of school. Dropping out and repeating the class are competing risks; repeating one particular class is not competing with having repeated other classes before or going to repeat another class afterwards.

 

The specific problem I have deals with events that may hinder school progress for children of school age. They may fail to enroll at the normal age, most of which finally enroll albeit at a later age; they may have repeated one or more classes (because they failed to pass it the previous year), or may have dropped out of school.

 

I wish to model the chances of adverse events along the “school history” of a typical child, in terms of the age (or level of education) at which these events may happen.

 

To make things a little more complicated, I do not have in this case a longitudinal study, but a cross section of kids to whom the events have already  happened. The cross section information available is census data for an entire, albeit relatively small [developing] country, so statistical significance in the usual sense is not a problem (tens or hundreds of thousands of kids in each situation). Covariates include household-family variables (SES, education of adults, etc) and characteristics of the child (age, gender,  educational attainment up to the event, child work if any, etc). Some of these covariates might be treated as time-dependent, but this might be (hopefully) avoided.

 

Thanks in advance

 

Hector

 


NOTICE: This e-mail (and any attachments) may contain PRIVILEGED OR CONFIDENTIAL information and is intended only for the use of the specific individual(s) to whom it is addressed. It may contain information that is privileged and confidential under state and federal law. This information may be used or disclosed only in accordance with law, and you may be subject to penalties under law for improper use or further disclosure of the information in this e-mail and its attachments. If you have received this e-mail in error, please immediately notify the person named above by reply e-mail, and then delete the original e-mail. Thank you.

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Re: Recurrent events in survival analysis

Bruce Weaver
Administrator
Hi Fermin.  I have the Singer & Willett book, but have not yet read all of the chapters on time-to-event models--I left off somewhere in chapter 13 the last time I was reading it.  When I consult the table of contents, though, I see that they do discuss "competing risk" models in chapter 15 ("Extending the Cox Regression Model").  AFAIK, in competing risk models, each subject still "die" only once, but it can be for different reasons.  S&W give examples of students leaving school either by graduating or quitting, employers leaving through lay-off, quitting, or getting sacked, etc.  But this is not what Hector wants.  He has a "type of event that may happen several times to a single subject".  Are you sure Singer & Willett discuss that type of model?  Thanks for clarifying.

Cheers,
Bruce

Ornelas, Fermin-2 wrote
Hector:
You may want to check their web site for the book Applied Longitudinal Analysis. I think they have both SAS and SPSS coding.

Fermin Ornelas, Ph.D.

From: Hector Maletta [mailto:hmaletta@fibertel.com.ar]
Sent: Monday, October 25, 2010 12:46 PM
To: Ornelas, Fermin; SPSSX-L@LISTSERV.UGA.EDU
Subject: RE: Recurrent events in survival analysis

Thanks, Fermin. Will look at those articles. However,  have plenty of references for the matter itself. I was rather looking for software solutions (preferably within SPSS). Dale Glaser has contributed some specific suggestions in that direction.
Hector

De: Ornelas, Fermin [mailto:FerminOrnelas@azdes.gov]
Enviado el: Monday, October 25, 2010 3:56 PM
Para: 'Hector Maletta'; SPSSX-L@LISTSERV.UGA.EDU
Asunto: RE: Recurrent events in survival analysis

You may want to check some nice articles by Singer and Willet. They have researched this area very well.

Fermin Ornelas, Ph.D.

From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of Hector Maletta
Sent: Monday, October 25, 2010 9:28 AM
To: SPSSX-L@LISTSERV.UGA.EDU
Subject: Recurrent events in survival analysis

Is there any way in SPSS 19 to do a survival analysis (Cox Regression) for situations in which more than one event is analyzed? Any other accessible software?

This may include one single type of event that may happen several times to a single subject (e.g. getting ill or failing a class at school), or several different kinds of events that may or may not be competing, such as (1) repeating a given class in school after failure the previous year, and  (2) dropping out of school. Dropping out and repeating the class are competing risks; repeating one particular class is not competing with having repeated other classes before or going to repeat another class afterwards.

The specific problem I have deals with events that may hinder school progress for children of school age. They may fail to enroll at the normal age, most of which finally enroll albeit at a later age; they may have repeated one or more classes (because they failed to pass it the previous year), or may have dropped out of school.

I wish to model the chances of adverse events along the "school history" of a typical child, in terms of the age (or level of education) at which these events may happen.

To make things a little more complicated, I do not have in this case a longitudinal study, but a cross section of kids to whom the events have already  happened. The cross section information available is census data for an entire, albeit relatively small [developing] country, so statistical significance in the usual sense is not a problem (tens or hundreds of thousands of kids in each situation). Covariates include household-family variables (SES, education of adults, etc) and characteristics of the child (age, gender,  educational attainment up to the event, child work if any, etc). Some of these covariates might be treated as time-dependent, but this might be (hopefully) avoided.

Thanks in advance

Hector

________________________________
NOTICE: This e-mail (and any attachments) may contain PRIVILEGED OR CONFIDENTIAL information and is intended only for the use of the specific individual(s) to whom it is addressed. It may contain information that is privileged and confidential under state and federal law. This information may be used or disclosed only in accordance with law, and you may be subject to penalties under law for improper use or further disclosure of the information in this e-mail and its attachments. If you have received this e-mail in error, please immediately notify the person named above by reply e-mail, and then delete the original e-mail. Thank you.

Se certificó que el correo entrante no contiene virus.
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--
Bruce Weaver
bweaver@lakeheadu.ca
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

NOTE: My Hotmail account is not monitored regularly.
To send me an e-mail, please use the address shown above.
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Re: Recurrent events in survival analysis

Ornelas, Fermin-2
Bruce:

I just got the book last week so I am not ready to give further details on its contents. I am embarking on a recidivism project and would have to read it, once I do it I will have a better idea.

Fermin Ornelas

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Bruce Weaver
Sent: Monday, October 25, 2010 2:50 PM
To: [hidden email]
Subject: Re: Recurrent events in survival analysis

Hi Fermin.  I have the Singer & Willett book, but have not yet read all of
the chapters on time-to-event models--I left off somewhere in chapter 13 the
last time I was reading it.  When I consult the table of contents, though, I
see that they do discuss "competing risk" models in chapter 15 ("Extending
the Cox Regression Model").  AFAIK, in competing risk models, each subject
still "die" only once, but it can be for different reasons.  S&W give
examples of students leaving school either by graduating or quitting,
employers leaving through lay-off, quitting, or getting sacked, etc.  But
this is not what Hector wants.  He has a "type of event that may happen
several times to a single subject".  Are you sure Singer & Willett discuss
that type of model?  Thanks for clarifying.

Cheers,
Bruce


Ornelas, Fermin-2 wrote:

>
> Hector:
> You may want to check their web site for the book Applied Longitudinal
> Analysis. I think they have both SAS and SPSS coding.
>
> Fermin Ornelas, Ph.D.
>
> From: Hector Maletta [mailto:[hidden email]]
> Sent: Monday, October 25, 2010 12:46 PM
> To: Ornelas, Fermin; [hidden email]
> Subject: RE: Recurrent events in survival analysis
>
> Thanks, Fermin. Will look at those articles. However,  have plenty of
> references for the matter itself. I was rather looking for software
> solutions (preferably within SPSS). Dale Glaser has contributed some
> specific suggestions in that direction.
> Hector
>
> De: Ornelas, Fermin [mailto:[hidden email]]
> Enviado el: Monday, October 25, 2010 3:56 PM
> Para: 'Hector Maletta'; [hidden email]
> Asunto: RE: Recurrent events in survival analysis
>
> You may want to check some nice articles by Singer and Willet. They have
> researched this area very well.
>
> Fermin Ornelas, Ph.D.
>
> From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of
> Hector Maletta
> Sent: Monday, October 25, 2010 9:28 AM
> To: [hidden email]
> Subject: Recurrent events in survival analysis
>
> Is there any way in SPSS 19 to do a survival analysis (Cox Regression) for
> situations in which more than one event is analyzed? Any other accessible
> software?
>
> This may include one single type of event that may happen several times to
> a single subject (e.g. getting ill or failing a class at school), or
> several different kinds of events that may or may not be competing, such
> as (1) repeating a given class in school after failure the previous year,
> and  (2) dropping out of school. Dropping out and repeating the class are
> competing risks; repeating one particular class is not competing with
> having repeated other classes before or going to repeat another class
> afterwards.
>
> The specific problem I have deals with events that may hinder school
> progress for children of school age. They may fail to enroll at the normal
> age, most of which finally enroll albeit at a later age; they may have
> repeated one or more classes (because they failed to pass it the previous
> year), or may have dropped out of school.
>
> I wish to model the chances of adverse events along the "school history"
> of a typical child, in terms of the age (or level of education) at which
> these events may happen.
>
> To make things a little more complicated, I do not have in this case a
> longitudinal study, but a cross section of kids to whom the events have
> already  happened. The cross section information available is census data
> for an entire, albeit relatively small [developing] country, so
> statistical significance in the usual sense is not a problem (tens or
> hundreds of thousands of kids in each situation). Covariates include
> household-family variables (SES, education of adults, etc) and
> characteristics of the child (age, gender,  educational attainment up to
> the event, child work if any, etc). Some of these covariates might be
> treated as time-dependent, but this might be (hopefully) avoided.
>
> Thanks in advance
>
> Hector
>
> ________________________________
> NOTICE: This e-mail (and any attachments) may contain PRIVILEGED OR
> CONFIDENTIAL information and is intended only for the use of the specific
> individual(s) to whom it is addressed. It may contain information that is
> privileged and confidential under state and federal law. This information
> may be used or disclosed only in accordance with law, and you may be
> subject to penalties under law for improper use or further disclosure of
> the information in this e-mail and its attachments. If you have received
> this e-mail in error, please immediately notify the person named above by
> reply e-mail, and then delete the original e-mail. Thank you.
>
> Se certificó que el correo entrante no contiene virus.
> Comprobada por AVG - www.avg.es
> Versión: 8.5.448 / Base de datos de virus: 271.1.1/3206 - Fecha de la
> versión: 10/24/10 06:34:00
>
>


-----
--
Bruce Weaver
[hidden email]
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

NOTE: My Hotmail account is not monitored regularly.
To send me an e-mail, please use the address shown above.

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Re: Recurrent events in survival analysis

Hector Maletta
One book specifically discussing models for recurrent events and non competing risks is Modeling Survival Data: Extending the Cox Model, by T. M. Therneau and Patricia Grambsch (Springer, 2000). Includes S-Plus and SAS code, but no SPSS. Besides, it is 10 years old and may be somewhat dated by now. Some R code exists for similar purposes, as in the links suggested by Dale Glaser in this same thread.
All these texts assume a longitudinal data structure, in which the dates of all successive events are known for every subject; AFAIK none discusses a similar model using cross sectional data, in which you only have people of different ages (or different education levels) having or not having quitted school, or still attending school but in a class behind their age.
My own data comprise children of various ages, each belonging to one of several categories: those that never enrolled, those attending the normal or expected class for their age, others attending a class inferior to their age, dropouts, and those who have already finished senior high school (normally at about 17-18 years of age). All these groups of children (except the first and last categories) may have different levels of education attainment.
The model I wish to build may use chronological age or school attainment as the "time" variable for the survival analysis; whichever of these is chosen as the time variable, the other one may be a covariate in the model.
The events of interest are enrolling (or failing to enroll), getting one grade (or one additional grade) behind their age, and dropping out. These events may happen at any chronological age; not enrolling precludes dropping out, but if you enroll the other events are all possible, and may happen at various times.
If you fail to enroll, or after you drop out, you keep falling behind (one more grade per year). Those who finish (i.e. graduate from senior high) are censored, and are no longer at risk (as far as primary and secondary education is concerned).
A child may have fallen behind by enrolling at a late age, or for other reasons (repeating a grade, or temporarily leaving school); they can fall one (additional) grade behind more than one time, and thus may be one, two or more years below their age-adequate grade (in my dataset I got some guys in their late teens who are attending the first 1-3 grades of primary school, probably at a remedial school, and are therefore about ten years behind their age).

Altogether a very interesting problem, and possibly a real headache if I fail to get an adequate software very soon.

Hector

-----Mensaje original-----
De: SPSSX(r) Discussion [mailto:[hidden email]] En nombre de Ornelas, Fermin
Enviado el: Monday, October 25, 2010 7:04 PM
Para: [hidden email]
Asunto: Re: Recurrent events in survival analysis

Bruce:

I just got the book last week so I am not ready to give further details on its contents. I am embarking on a recidivism project and would have to read it, once I do it I will have a better idea.

Fermin Ornelas

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Bruce Weaver
Sent: Monday, October 25, 2010 2:50 PM
To: [hidden email]
Subject: Re: Recurrent events in survival analysis

Hi Fermin.  I have the Singer & Willett book, but have not yet read all of
the chapters on time-to-event models--I left off somewhere in chapter 13 the
last time I was reading it.  When I consult the table of contents, though, I
see that they do discuss "competing risk" models in chapter 15 ("Extending
the Cox Regression Model").  AFAIK, in competing risk models, each subject
still "die" only once, but it can be for different reasons.  S&W give
examples of students leaving school either by graduating or quitting,
employers leaving through lay-off, quitting, or getting sacked, etc.  But
this is not what Hector wants.  He has a "type of event that may happen
several times to a single subject".  Are you sure Singer & Willett discuss
that type of model?  Thanks for clarifying.

Cheers,
Bruce


Ornelas, Fermin-2 wrote:

>
> Hector:
> You may want to check their web site for the book Applied Longitudinal
> Analysis. I think they have both SAS and SPSS coding.
>
> Fermin Ornelas, Ph.D.
>
> From: Hector Maletta [mailto:[hidden email]]
> Sent: Monday, October 25, 2010 12:46 PM
> To: Ornelas, Fermin; [hidden email]
> Subject: RE: Recurrent events in survival analysis
>
> Thanks, Fermin. Will look at those articles. However,  have plenty of
> references for the matter itself. I was rather looking for software
> solutions (preferably within SPSS). Dale Glaser has contributed some
> specific suggestions in that direction.
> Hector
>
> De: Ornelas, Fermin [mailto:[hidden email]]
> Enviado el: Monday, October 25, 2010 3:56 PM
> Para: 'Hector Maletta'; [hidden email]
> Asunto: RE: Recurrent events in survival analysis
>
> You may want to check some nice articles by Singer and Willet. They have
> researched this area very well.
>
> Fermin Ornelas, Ph.D.
>
> From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of
> Hector Maletta
> Sent: Monday, October 25, 2010 9:28 AM
> To: [hidden email]
> Subject: Recurrent events in survival analysis
>
> Is there any way in SPSS 19 to do a survival analysis (Cox Regression) for
> situations in which more than one event is analyzed? Any other accessible
> software?
>
> This may include one single type of event that may happen several times to
> a single subject (e.g. getting ill or failing a class at school), or
> several different kinds of events that may or may not be competing, such
> as (1) repeating a given class in school after failure the previous year,
> and  (2) dropping out of school. Dropping out and repeating the class are
> competing risks; repeating one particular class is not competing with
> having repeated other classes before or going to repeat another class
> afterwards.
>
> The specific problem I have deals with events that may hinder school
> progress for children of school age. They may fail to enroll at the normal
> age, most of which finally enroll albeit at a later age; they may have
> repeated one or more classes (because they failed to pass it the previous
> year), or may have dropped out of school.
>
> I wish to model the chances of adverse events along the "school history"
> of a typical child, in terms of the age (or level of education) at which
> these events may happen.
>
> To make things a little more complicated, I do not have in this case a
> longitudinal study, but a cross section of kids to whom the events have
> already  happened. The cross section information available is census data
> for an entire, albeit relatively small [developing] country, so
> statistical significance in the usual sense is not a problem (tens or
> hundreds of thousands of kids in each situation). Covariates include
> household-family variables (SES, education of adults, etc) and
> characteristics of the child (age, gender,  educational attainment up to
> the event, child work if any, etc). Some of these covariates might be
> treated as time-dependent, but this might be (hopefully) avoided.
>
> Thanks in advance
>
> Hector
>
> ________________________________
> NOTICE: This e-mail (and any attachments) may contain PRIVILEGED OR
> CONFIDENTIAL information and is intended only for the use of the specific
> individual(s) to whom it is addressed. It may contain information that is
> privileged and confidential under state and federal law. This information
> may be used or disclosed only in accordance with law, and you may be
> subject to penalties under law for improper use or further disclosure of
> the information in this e-mail and its attachments. If you have received
> this e-mail in error, please immediately notify the person named above by
> reply e-mail, and then delete the original e-mail. Thank you.
>
> Se certificó que el correo entrante no contiene virus.
> Comprobada por AVG - www.avg.es
> Versión: 8.5.448 / Base de datos de virus: 271.1.1/3206 - Fecha de la
> versión: 10/24/10 06:34:00
>
>


-----
--
Bruce Weaver
[hidden email]
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

NOTE: My Hotmail account is not monitored regularly.
To send me an e-mail, please use the address shown above.

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Re: Recurrent events in survival analysis

Ornelas, Fermin-2
Thanks Hector, I check this reference too.

Fermin Ornelas

-----Original Message-----
From: Hector Maletta [mailto:[hidden email]]
Sent: Monday, October 25, 2010 4:48 PM
To: Ornelas, Fermin; [hidden email]
Subject: RE: Recurrent events in survival analysis

One book specifically discussing models for recurrent events and non competing risks is Modeling Survival Data: Extending the Cox Model, by T. M. Therneau and Patricia Grambsch (Springer, 2000). Includes S-Plus and SAS code, but no SPSS. Besides, it is 10 years old and may be somewhat dated by now. Some R code exists for similar purposes, as in the links suggested by Dale Glaser in this same thread.
All these texts assume a longitudinal data structure, in which the dates of all successive events are known for every subject; AFAIK none discusses a similar model using cross sectional data, in which you only have people of different ages (or different education levels) having or not having quitted school, or still attending school but in a class behind their age.
My own data comprise children of various ages, each belonging to one of several categories: those that never enrolled, those attending the normal or expected class for their age, others attending a class inferior to their age, dropouts, and those who have already finished senior high school (normally at about 17-18 years of age). All these groups of children (except the first and last categories) may have different levels of education attainment.
The model I wish to build may use chronological age or school attainment as the "time" variable for the survival analysis; whichever of these is chosen as the time variable, the other one may be a covariate in the model.
The events of interest are enrolling (or failing to enroll), getting one grade (or one additional grade) behind their age, and dropping out. These events may happen at any chronological age; not enrolling precludes dropping out, but if you enroll the other events are all possible, and may happen at various times.
If you fail to enroll, or after you drop out, you keep falling behind (one more grade per year). Those who finish (i.e. graduate from senior high) are censored, and are no longer at risk (as far as primary and secondary education is concerned).
A child may have fallen behind by enrolling at a late age, or for other reasons (repeating a grade, or temporarily leaving school); they can fall one (additional) grade behind more than one time, and thus may be one, two or more years below their age-adequate grade (in my dataset I got some guys in their late teens who are attending the first 1-3 grades of primary school, probably at a remedial school, and are therefore about ten years behind their age).

Altogether a very interesting problem, and possibly a real headache if I fail to get an adequate software very soon.

Hector

-----Mensaje original-----
De: SPSSX(r) Discussion [mailto:[hidden email]] En nombre de Ornelas, Fermin
Enviado el: Monday, October 25, 2010 7:04 PM
Para: [hidden email]
Asunto: Re: Recurrent events in survival analysis

Bruce:

I just got the book last week so I am not ready to give further details on its contents. I am embarking on a recidivism project and would have to read it, once I do it I will have a better idea.

Fermin Ornelas

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Bruce Weaver
Sent: Monday, October 25, 2010 2:50 PM
To: [hidden email]
Subject: Re: Recurrent events in survival analysis

Hi Fermin.  I have the Singer & Willett book, but have not yet read all of
the chapters on time-to-event models--I left off somewhere in chapter 13 the
last time I was reading it.  When I consult the table of contents, though, I
see that they do discuss "competing risk" models in chapter 15 ("Extending
the Cox Regression Model").  AFAIK, in competing risk models, each subject
still "die" only once, but it can be for different reasons.  S&W give
examples of students leaving school either by graduating or quitting,
employers leaving through lay-off, quitting, or getting sacked, etc.  But
this is not what Hector wants.  He has a "type of event that may happen
several times to a single subject".  Are you sure Singer & Willett discuss
that type of model?  Thanks for clarifying.

Cheers,
Bruce


Ornelas, Fermin-2 wrote:

>
> Hector:
> You may want to check their web site for the book Applied Longitudinal
> Analysis. I think they have both SAS and SPSS coding.
>
> Fermin Ornelas, Ph.D.
>
> From: Hector Maletta [mailto:[hidden email]]
> Sent: Monday, October 25, 2010 12:46 PM
> To: Ornelas, Fermin; [hidden email]
> Subject: RE: Recurrent events in survival analysis
>
> Thanks, Fermin. Will look at those articles. However,  have plenty of
> references for the matter itself. I was rather looking for software
> solutions (preferably within SPSS). Dale Glaser has contributed some
> specific suggestions in that direction.
> Hector
>
> De: Ornelas, Fermin [mailto:[hidden email]]
> Enviado el: Monday, October 25, 2010 3:56 PM
> Para: 'Hector Maletta'; [hidden email]
> Asunto: RE: Recurrent events in survival analysis
>
> You may want to check some nice articles by Singer and Willet. They have
> researched this area very well.
>
> Fermin Ornelas, Ph.D.
>
> From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of
> Hector Maletta
> Sent: Monday, October 25, 2010 9:28 AM
> To: [hidden email]
> Subject: Recurrent events in survival analysis
>
> Is there any way in SPSS 19 to do a survival analysis (Cox Regression) for
> situations in which more than one event is analyzed? Any other accessible
> software?
>
> This may include one single type of event that may happen several times to
> a single subject (e.g. getting ill or failing a class at school), or
> several different kinds of events that may or may not be competing, such
> as (1) repeating a given class in school after failure the previous year,
> and  (2) dropping out of school. Dropping out and repeating the class are
> competing risks; repeating one particular class is not competing with
> having repeated other classes before or going to repeat another class
> afterwards.
>
> The specific problem I have deals with events that may hinder school
> progress for children of school age. They may fail to enroll at the normal
> age, most of which finally enroll albeit at a later age; they may have
> repeated one or more classes (because they failed to pass it the previous
> year), or may have dropped out of school.
>
> I wish to model the chances of adverse events along the "school history"
> of a typical child, in terms of the age (or level of education) at which
> these events may happen.
>
> To make things a little more complicated, I do not have in this case a
> longitudinal study, but a cross section of kids to whom the events have
> already  happened. The cross section information available is census data
> for an entire, albeit relatively small [developing] country, so
> statistical significance in the usual sense is not a problem (tens or
> hundreds of thousands of kids in each situation). Covariates include
> household-family variables (SES, education of adults, etc) and
> characteristics of the child (age, gender,  educational attainment up to
> the event, child work if any, etc). Some of these covariates might be
> treated as time-dependent, but this might be (hopefully) avoided.
>
> Thanks in advance
>
> Hector
>
> ________________________________
> NOTICE: This e-mail (and any attachments) may contain PRIVILEGED OR
> CONFIDENTIAL information and is intended only for the use of the specific
> individual(s) to whom it is addressed. It may contain information that is
> privileged and confidential under state and federal law. This information
> may be used or disclosed only in accordance with law, and you may be
> subject to penalties under law for improper use or further disclosure of
> the information in this e-mail and its attachments. If you have received
> this e-mail in error, please immediately notify the person named above by
> reply e-mail, and then delete the original e-mail. Thank you.
>
> Se certificó que el correo entrante no contiene virus.
> Comprobada por AVG - www.avg.es
> Versión: 8.5.448 / Base de datos de virus: 271.1.1/3206 - Fecha de la
> versión: 10/24/10 06:34:00
>
>


-----
--
Bruce Weaver
[hidden email]
http://sites.google.com/a/lakeheadu.ca/bweaver/

"When all else fails, RTFM."

NOTE: My Hotmail account is not monitored regularly.
To send me an e-mail, please use the address shown above.

--
View this message in context: http://spssx-discussion.1045642.n5.nabble.com/Recurrent-events-in-survival-analysis-tp3235690p3236285.html
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Re: Recurrent events in survival analysis

Art Kendall
With regard to "a child being a grade behind his/her age", there is
other noise in the measurement that you may want to keep in mind.
In different jurisdictions there are different date-of-birth criteria
for entering school.  So in many analyses a child born on or before the
local criterion date will be in grade n, whereas, a child born the very
next day will be the same age but in grade n-1.  Without any children
from the same jurisdiction being "held back" there could be something
like 364 days between the birth of the oldest child and the youngest
child in a class. There also would be noise due to children starting in
different jurisdictions and moving.

In some jurisdictions  a child can "skip" a grade.

I don't know if it is still true, but some jurisdictions used to have
half-year systems.
Both halves of the grade would be going on at the same time, i.e., in
September some children are entering the first half of a grade and some
are entering the second half.  Systems with half-year systems had 2
criterion dates for entry.  Also a child could be "kept back" or "skip"
half a grade.

In addition, within some jurisdictions the criterion date changes from
year to year.


Art Kendall
Social Research Consultants


On 10/28/2010 11:30 AM, Ornelas, Fermin wrote:

> Thanks Hector, I check this reference too.
>
> Fermin Ornelas
>
> -----Original Message-----
> From: Hector Maletta [mailto:[hidden email]]
> Sent: Monday, October 25, 2010 4:48 PM
> To: Ornelas, Fermin; [hidden email]
> Subject: RE: Recurrent events in survival analysis
>
> One book specifically discussing models for recurrent events and non competing risks is Modeling Survival Data: Extending the Cox Model, by T. M. Therneau and Patricia Grambsch (Springer, 2000). Includes S-Plus and SAS code, but no SPSS. Besides, it is 10 years old and may be somewhat dated by now. Some R code exists for similar purposes, as in the links suggested by Dale Glaser in this same thread.
> All these texts assume a longitudinal data structure, in which the dates of all successive events are known for every subject; AFAIK none discusses a similar model using cross sectional data, in which you only have people of different ages (or different education levels) having or not having quitted school, or still attending school but in a class behind their age.
> My own data comprise children of various ages, each belonging to one of several categories: those that never enrolled, those attending the normal or expected class for their age, others attending a class inferior to their age, dropouts, and those who have already finished senior high school (normally at about 17-18 years of age). All these groups of children (except the first and last categories) may have different levels of education attainment.
> The model I wish to build may use chronological age or school attainment as the "time" variable for the survival analysis; whichever of these is chosen as the time variable, the other one may be a covariate in the model.
> The events of interest are enrolling (or failing to enroll), getting one grade (or one additional grade) behind their age, and dropping out. These events may happen at any chronological age; not enrolling precludes dropping out, but if you enroll the other events are all possible, and may happen at various times.
> If you fail to enroll, or after you drop out, you keep falling behind (one more grade per year). Those who finish (i.e. graduate from senior high) are censored, and are no longer at risk (as far as primary and secondary education is concerned).
> A child may have fallen behind by enrolling at a late age, or for other reasons (repeating a grade, or temporarily leaving school); they can fall one (additional) grade behind more than one time, and thus may be one, two or more years below their age-adequate grade (in my dataset I got some guys in their late teens who are attending the first 1-3 grades of primary school, probably at a remedial school, and are therefore about ten years behind their age).
>
> Altogether a very interesting problem, and possibly a real headache if I fail to get an adequate software very soon.
>
> Hector
>
> -----Mensaje original-----
> De: SPSSX(r) Discussion [mailto:[hidden email]] En nombre de Ornelas, Fermin
> Enviado el: Monday, October 25, 2010 7:04 PM
> Para: [hidden email]
> Asunto: Re: Recurrent events in survival analysis
>
> Bruce:
>
> I just got the book last week so I am not ready to give further details on its contents. I am embarking on a recidivism project and would have to read it, once I do it I will have a better idea.
>
> Fermin Ornelas
>
> -----Original Message-----
> From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Bruce Weaver
> Sent: Monday, October 25, 2010 2:50 PM
> To: [hidden email]
> Subject: Re: Recurrent events in survival analysis
>
> Hi Fermin.  I have the Singer&  Willett book, but have not yet read all of
> the chapters on time-to-event models--I left off somewhere in chapter 13 the
> last time I was reading it.  When I consult the table of contents, though, I
> see that they do discuss "competing risk" models in chapter 15 ("Extending
> the Cox Regression Model").  AFAIK, in competing risk models, each subject
> still "die" only once, but it can be for different reasons.  S&W give
> examples of students leaving school either by graduating or quitting,
> employers leaving through lay-off, quitting, or getting sacked, etc.  But
> this is not what Hector wants.  He has a "type of event that may happen
> several times to a single subject".  Are you sure Singer&  Willett discuss
> that type of model?  Thanks for clarifying.
>
> Cheers,
> Bruce
>
>
> Ornelas, Fermin-2 wrote:
>> Hector:
>> You may want to check their web site for the book Applied Longitudinal
>> Analysis. I think they have both SAS and SPSS coding.
>>
>> Fermin Ornelas, Ph.D.
>>
>> From: Hector Maletta [mailto:[hidden email]]
>> Sent: Monday, October 25, 2010 12:46 PM
>> To: Ornelas, Fermin; [hidden email]
>> Subject: RE: Recurrent events in survival analysis
>>
>> Thanks, Fermin. Will look at those articles. However,  have plenty of
>> references for the matter itself. I was rather looking for software
>> solutions (preferably within SPSS). Dale Glaser has contributed some
>> specific suggestions in that direction.
>> Hector
>>
>> De: Ornelas, Fermin [mailto:[hidden email]]
>> Enviado el: Monday, October 25, 2010 3:56 PM
>> Para: 'Hector Maletta'; [hidden email]
>> Asunto: RE: Recurrent events in survival analysis
>>
>> You may want to check some nice articles by Singer and Willet. They have
>> researched this area very well.
>>
>> Fermin Ornelas, Ph.D.
>>
>> From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of
>> Hector Maletta
>> Sent: Monday, October 25, 2010 9:28 AM
>> To: [hidden email]
>> Subject: Recurrent events in survival analysis
>>
>> Is there any way in SPSS 19 to do a survival analysis (Cox Regression) for
>> situations in which more than one event is analyzed? Any other accessible
>> software?
>>
>> This may include one single type of event that may happen several times to
>> a single subject (e.g. getting ill or failing a class at school), or
>> several different kinds of events that may or may not be competing, such
>> as (1) repeating a given class in school after failure the previous year,
>> and  (2) dropping out of school. Dropping out and repeating the class are
>> competing risks; repeating one particular class is not competing with
>> having repeated other classes before or going to repeat another class
>> afterwards.
>>
>> The specific problem I have deals with events that may hinder school
>> progress for children of school age. They may fail to enroll at the normal
>> age, most of which finally enroll albeit at a later age; they may have
>> repeated one or more classes (because they failed to pass it the previous
>> year), or may have dropped out of school.
>>
>> I wish to model the chances of adverse events along the "school history"
>> of a typical child, in terms of the age (or level of education) at which
>> these events may happen.
>>
>> To make things a little more complicated, I do not have in this case a
>> longitudinal study, but a cross section of kids to whom the events have
>> already  happened. The cross section information available is census data
>> for an entire, albeit relatively small [developing] country, so
>> statistical significance in the usual sense is not a problem (tens or
>> hundreds of thousands of kids in each situation). Covariates include
>> household-family variables (SES, education of adults, etc) and
>> characteristics of the child (age, gender,  educational attainment up to
>> the event, child work if any, etc). Some of these covariates might be
>> treated as time-dependent, but this might be (hopefully) avoided.
>>
>> Thanks in advance
>>
>> Hector
>>
>> ________________________________
>> NOTICE: This e-mail (and any attachments) may contain PRIVILEGED OR
>> CONFIDENTIAL information and is intended only for the use of the specific
>> individual(s) to whom it is addressed. It may contain information that is
>> privileged and confidential under state and federal law. This information
>> may be used or disclosed only in accordance with law, and you may be
>> subject to penalties under law for improper use or further disclosure of
>> the information in this e-mail and its attachments. If you have received
>> this e-mail in error, please immediately notify the person named above by
>> reply e-mail, and then delete the original e-mail. Thank you.
>>
>> Se certificó que el correo entrante no contiene virus.
>> Comprobada por AVG - www.avg.es
>> Versión: 8.5.448 / Base de datos de virus: 271.1.1/3206 - Fecha de la
>> versión: 10/24/10 06:34:00
>>
>>
>
> -----
> --
> Bruce Weaver
> [hidden email]
> http://sites.google.com/a/lakeheadu.ca/bweaver/
>
> "When all else fails, RTFM."
>
> NOTE: My Hotmail account is not monitored regularly.
> To send me an e-mail, please use the address shown above.
>
> --
> View this message in context: http://spssx-discussion.1045642.n5.nabble.com/Recurrent-events-in-survival-analysis-tp3235690p3236285.html
> Sent from the SPSSX Discussion mailing list archive at Nabble.com.
>
> =====================
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> [hidden email] (not to SPSSX-L), with no body text except the
> command. To leave the list, send the command
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>
>
> NOTICE: This e-mail (and any attachments) may contain PRIVILEGED OR CONFIDENTIAL information and is intended only for the use of the specific individual(s) to whom it is addressed.  It may contain information that is privileged and confidential under state and federal law.  This information may be used or disclosed only in accordance with law, and you may be subject to penalties under law for improper use or further disclosure of the information in this e-mail and its attachments. If you have received this e-mail in error, please immediately notify the person named above by reply e-mail, and then delete the original e-mail.  Thank you.
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Art Kendall
Social Research Consultants
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Re: Recurrent events in survival analysis

Hector Maletta
In reply to this post by Hector Maletta
Quite true, Art, and thank you for raising the issue.
No half year regimes in the country I am analyzing, but certainly fuzziness when the age of children is measured in years. The normal enrolment age is 6, but 20% of children aged 5 are already in school, and some children aged 7 are in first grade. As no further precision exists in the data, one has to make a choice. A strict definition of being "behind" would be that the grade currently attended is lower than (age-6), but this would tend to overstate the number of  "delayed" children. A more conservative definition would be allowing for children aged 7 to be in first grade without being considered as "too old for that grade", but this risks missing some children who are 7 and are already "delayed" (same uncertainty applies to older children who are or fail to be in higher grades).
However, with any definition, the problem is that "being delayed by an additional year" is an event that may happen more than one time, along with other events such as dropping out of school (which may happen at any age and any grade). A multiple-event model is required (including recurrent events of the same type, and competing events such as dropping out --or dying, for that matter).
The R programs suggested before in this thread have a maximum number of cases (30,000 or 60,000) far below the size of my census data set, and are thus not applicable for my problem.

Hector

----- Mensaje original -----
De: Art Kendall <[hidden email]>
Fecha: Jueves, Octubre 28, 2010 1:42 pm
Asunto: Re: Recurrent events in survival analysis

> With regard to "a child being a grade behind his/her age", there is
> other noise in the measurement that you may want to keep in mind.
> In different jurisdictions there are different date-of-birth criteria
> for entering school.  So in many analyses a child born on or
> before the
> local criterion date will be in grade n, whereas, a child born the
> verynext day will be the same age but in grade n-1.  Without any
> childrenfrom the same jurisdiction being "held back" there could
> be something
> like 364 days between the birth of the oldest child and the youngest
> child in a class. There also would be noise due to children
> starting in
> different jurisdictions and moving.
>
> In some jurisdictions  a child can "skip" a grade.
>
> I don't know if it is still true, but some jurisdictions used to have
> half-year systems.
> Both halves of the grade would be going on at the same time, i.e., in
> September some children are entering the first half of a grade and
> someare entering the second half.  Systems with half-year systems
> had 2
> criterion dates for entry.  Also a child could be "kept back" or
> "skip"half a grade.
>
> In addition, within some jurisdictions the criterion date changes from
> year to year.
>
>
> Art Kendall
> Social Research Consultants
>
>
> On 10/28/2010 11:30 AM, Ornelas, Fermin wrote:
> > Thanks Hector, I check this reference too.
> >
> > Fermin Ornelas
> >
> > -----Original Message-----
> > From: Hector Maletta [[hidden email]]
> > Sent: Monday, October 25, 2010 4:48 PM
> > To: Ornelas, Fermin; [hidden email]
> > Subject: RE: Recurrent events in survival analysis
> >
> > One book specifically discussing models for recurrent events and
> non competing risks is Modeling Survival Data: Extending the Cox
> Model, by T. M. Therneau and Patricia Grambsch (Springer, 2000).
> Includes S-Plus and SAS code, but no SPSS. Besides, it is 10 years
> old and may be somewhat dated by now. Some R code exists for
> similar purposes, as in the links suggested by Dale Glaser in this
> same thread.
> > All these texts assume a longitudinal data structure, in which
> the dates of all successive events are known for every subject;
> AFAIK none discusses a similar model using cross sectional data,
> in which you only have people of different ages (or different
> education levels) having or not having quitted school, or still
> attending school but in a class behind their age.
> > My own data comprise children of various ages, each belonging to
> one of several categories: those that never enrolled, those
> attending the normal or expected class for their age, others
> attending a class inferior to their age, dropouts, and those who
> have already finished senior high school (normally at about 17-18
> years of age). All these groups of children (except the first and
> last categories) may have different levels of education attainment.
> > The model I wish to build may use chronological age or school
> attainment as the "time" variable for the survival analysis;
> whichever of these is chosen as the time variable, the other one
> may be a covariate in the model.
> > The events of interest are enrolling (or failing to enroll),
> getting one grade (or one additional grade) behind their age, and
> dropping out. These events may happen at any chronological age;
> not enrolling precludes dropping out, but if you enroll the other
> events are all possible, and may happen at various times.
> > If you fail to enroll, or after you drop out, you keep falling
> behind (one more grade per year). Those who finish (i.e. graduate
> from senior high) are censored, and are no longer at risk (as far
> as primary and secondary education is concerned).
> > A child may have fallen behind by enrolling at a late age, or
> for other reasons (repeating a grade, or temporarily leaving
> school); they can fall one (additional) grade behind more than one
> time, and thus may be one, two or more years below their age-
> adequate grade (in my dataset I got some guys in their late teens
> who are attending the first 1-3 grades of primary school, probably
> at a remedial school, and are therefore about ten years behind
> their age).
> >
> > Altogether a very interesting problem, and possibly a real
> headache if I fail to get an adequate software very soon.
> >
> > Hector
> >
> > -----Mensaje original-----
> > De: SPSSX(r) Discussion [[hidden email]] En nombre de
> Ornelas, Fermin
> > Enviado el: Monday, October 25, 2010 7:04 PM
> > Para: [hidden email]
> > Asunto: Re: Recurrent events in survival analysis
> >
> > Bruce:
> >
> > I just got the book last week so I am not ready to give further
> details on its contents. I am embarking on a recidivism project
> and would have to read it, once I do it I will have a better idea.
> >
> > Fermin Ornelas
> >
> > -----Original Message-----
> > From: SPSSX(r) Discussion [[hidden email]] On Behalf
> Of Bruce Weaver
> > Sent: Monday, October 25, 2010 2:50 PM
> > To: [hidden email]
> > Subject: Re: Recurrent events in survival analysis
> >
> > Hi Fermin.  I have the Singer&  Willett book, but have not yet
> read all of
> > the chapters on time-to-event models--I left off somewhere in
> chapter 13 the
> > last time I was reading it.  When I consult the table of
> contents, though, I
> > see that they do discuss "competing risk" models in chapter 15
> ("Extending> the Cox Regression Model").  AFAIK, in competing risk
> models, each subject
> > still "die" only once, but it can be for different reasons.  S&W
> give> examples of students leaving school either by graduating or
> quitting,> employers leaving through lay-off, quitting, or getting
> sacked, etc.  But
> > this is not what Hector wants.  He has a "type of event that may
> happen> several times to a single subject".  Are you sure Singer&
> Willett discuss
> > that type of model?  Thanks for clarifying.
> >
> > Cheers,
> > Bruce
> >
> >
> > Ornelas, Fermin-2 wrote:
> >> Hector:
> >> You may want to check their web site for the book Applied
> Longitudinal>> Analysis. I think they have both SAS and SPSS coding.
> >>
> >> Fermin Ornelas, Ph.D.
> >>
> >> From: Hector Maletta [[hidden email]]
> >> Sent: Monday, October 25, 2010 12:46 PM
> >> To: Ornelas, Fermin; [hidden email]
> >> Subject: RE: Recurrent events in survival analysis
> >>
> >> Thanks, Fermin. Will look at those articles. However,  have
> plenty of
> >> references for the matter itself. I was rather looking for software
> >> solutions (preferably within SPSS). Dale Glaser has contributed
> some>> specific suggestions in that direction.
> >> Hector
> >>
> >> De: Ornelas, Fermin [[hidden email]]
> >> Enviado el: Monday, October 25, 2010 3:56 PM
> >> Para: 'Hector Maletta'; [hidden email]
> >> Asunto: RE: Recurrent events in survival analysis
> >>
> >> You may want to check some nice articles by Singer and Willet.
> They have
> >> researched this area very well.
> >>
> >> Fermin Ornelas, Ph.D.
> >>
> >> From: SPSSX(r) Discussion [[hidden email]] On Behalf Of
> >> Hector Maletta
> >> Sent: Monday, October 25, 2010 9:28 AM
> >> To: [hidden email]
> >> Subject: Recurrent events in survival analysis
> >>
> >> Is there any way in SPSS 19 to do a survival analysis (Cox
> Regression) for
> >> situations in which more than one event is analyzed? Any other
> accessible>> software?
> >>
> >> This may include one single type of event that may happen
> several times to
> >> a single subject (e.g. getting ill or failing a class at
> school), or
> >> several different kinds of events that may or may not be
> competing, such
> >> as (1) repeating a given class in school after failure the
> previous year,
> >> and  (2) dropping out of school. Dropping out and repeating the
> class are
> >> competing risks; repeating one particular class is not
> competing with
> >> having repeated other classes before or going to repeat another
> class>> afterwards.
> >>
> >> The specific problem I have deals with events that may hinder
> school>> progress for children of school age. They may fail to
> enroll at the normal
> >> age, most of which finally enroll albeit at a later age; they
> may have
> >> repeated one or more classes (because they failed to pass it
> the previous
> >> year), or may have dropped out of school.
> >>
> >> I wish to model the chances of adverse events along the "school
> history">> of a typical child, in terms of the age (or level of
> education) at which
> >> these events may happen.
> >>
> >> To make things a little more complicated, I do not have in this
> case a
> >> longitudinal study, but a cross section of kids to whom the
> events have
> >> already  happened. The cross section information available is
> census data
> >> for an entire, albeit relatively small [developing] country, so
> >> statistical significance in the usual sense is not a problem
> (tens or
> >> hundreds of thousands of kids in each situation). Covariates
> include>> household-family variables (SES, education of adults,
> etc) and
> >> characteristics of the child (age, gender,  educational
> attainment up to
> >> the event, child work if any, etc). Some of these covariates
> might be
> >> treated as time-dependent, but this might be (hopefully) avoided.
> >>
> >> Thanks in advance
> >>
> >> Hector
> >>
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> >>
> >
> > -----
> > --
> > Bruce Weaver
> > [hidden email]
> > http://sites.google.com/a/lakeheadu.ca/bweaver/
> >
> > "When all else fails, RTFM."
> >
> > NOTE: My Hotmail account is not monitored regularly.
> > To send me an e-mail, please use the address shown above.
> >
> > --
> > View this message in context: http://spssx-
> discussion.1045642.n5.nabble.com/Recurrent-events-in-survival-
> analysis-tp3235690p3236285.html
> > Sent from the SPSSX Discussion mailing list archive at Nabble.com.
> >
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