I am using a mixed model to assess the effects of various variables (i.e.
treatment, density, visibility) on bee behavior (e.g., avoidance frequency -
total avoidances per total visits; feeding frequency, and mating frequency).
Bee individuals is my random factor (n=63 different bees), whereas treatment
type, animal density, and air visibility are my fixed factors.
However, when I run my models, I immediately get an error that I cannot fix.
Here is a sample of my data:
Bee Treatment Visits Avoid Feeding Mating Density Visibility
1 C 5 0 5 0 5 4
2 C 4 0 3 0 5 4
3 C 3 0 3 0 5 4
...
63
1 PC 2 0 1 1 5 4
2 PC 3 0 0 3 5 4
3 PC 1 0 0 0 5 4
...
63
1 M 5 0 1 3 5 4
2 M 3 2 0 0 5 4
3 M 2 0 0 2 5 4
...
63One I create my .txt file, I being my coding in R by first loading lme4.
After that, my coding starts off as follows:
barrierdat = read.table("GLMMROW.txt", header=TRUE)
barrierdat
barrierdat$Visibility = as.factor(barrierdat$Visibility);
barrierdat$Density = as.factor(barrierdat$Density);
p01.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee),
family=poisson,
data=egghead); # null model;
p02.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee)+Treatment,
family=poisson,
data=egghead);
p03.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee)+Visibility,
family=poisson,
data=egghead);
p04.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee)+Density,
family=poisson,
data=egghead);However, upon immediately running my models
(e.g. p01.glmer), I receive the error:
Error: (maxstephalfit) PIRLS step-halvings failed to reduce deviance in
pwrssUpdate
Does anybody know what the issue is? I ran similar data several weeks ago and
had no issues. Any Suggestions on how to proceed?
[[alternative HTML version deleted]]
Dear Craig,
It is better to ask questions about lme4 at r-sig-mixed-models (in cc).
Are you using a recent version of lme4? Try upgrading lme4 and see if you still
get the error.
Best regards,
Thierry
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
+ 32 2 525 02 51
+ 32 54 43 61 85
Thierry.Onkelinx at inbo.be
www.inbo.be
To call in the statistician after the experiment is done may be no more than
asking him to perform a post-mortem examination: he may be able to say what the
experiment died of.
~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data.
~ Roger Brinner
The combination of some data and an aching desire for an answer does not ensure
that a reasonable answer can be extracted from a given body of data.
~ John Tukey
-----Oorspronkelijk bericht-----
Van: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
Namens Craig O'Connell
Verzonden: maandag 28 april 2014 3:20
Aan: r-help at r-project.org
Onderwerp: [R] lme4 Error Help: ?maxstephalfit?pwrssUpdate?
I am using a mixed model to assess the effects of various variables (i.e.
treatment, density, visibility) on bee behavior (e.g., avoidance frequency -
total avoidances per total visits; feeding frequency, and mating frequency).
Bee individuals is my random factor (n=63 different bees), whereas treatment
type, animal density, and air visibility are my fixed factors.
However, when I run my models, I immediately get an error that I cannot fix.
Here is a sample of my data:
Bee Treatment Visits Avoid Feeding Mating Density Visibility
1 C 5 0 5 0 5 4
2 C 4 0 3 0 5 4
3 C 3 0 3 0 5 4
...
63
1 PC 2 0 1 1 5 4
2 PC 3 0 0 3 5 4
3 PC 1 0 0 0 5 4
...
63
1 M 5 0 1 3 5 4
2 M 3 2 0 0 5 4
3 M 2 0 0 2 5 4
...
63One I create my .txt file, I being my coding in R by first loading lme4.
After that, my coding starts off as follows:
barrierdat = read.table("GLMMROW.txt", header=TRUE) barrierdat
barrierdat$Visibility = as.factor(barrierdat$Visibility);
barrierdat$Density = as.factor(barrierdat$Density);
p01.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee),
family=poisson,
data=egghead); # null model; p02.glmer =
glmer(Avoidance~offset(log(Visits))+(1|Bee)+Treatment, family=poisson,
data=egghead);
p03.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee)+Visibility,
family=poisson,
data=egghead);
p04.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee)+Density,
family=poisson,
data=egghead);However, upon immediately running my models
(e.g. p01.glmer), I receive the error:
Error: (maxstephalfit) PIRLS step-halvings failed to reduce deviance in
pwrssUpdate
Does anybody know what the issue is? I ran similar data several weeks ago and
had no issues. Any Suggestions on how to proceed?
[[alternative HTML version deleted]]
______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
* * * * * * * * * * * * * D I S C L A I M E R * * * * * * * * * * * * *
Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer en
binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is
door een geldig ondertekend document.
The views expressed in this message and any annex are purely those of the writer
and may not be regarded as stating an official position of INBO, as long as the
message is not confirmed by a duly signed document.
Dear Craig,
It is better to ask questions about lme4 at r-sig-mixed-models (in cc).
Are you using a recent version of lme4? Try upgrading lme4 and see if you still
get the error.
Best regards,
Thierry
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
+ 32 2 525 02 51
+ 32 54 43 61 85
Thierry.Onkelinx@inbo.be
www.inbo.be
To call in the statistician after the experiment is done may be no more than
asking him to perform a post-mortem examination: he may be able to say what the
experiment died of.
~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data.
~ Roger Brinner
The combination of some data and an aching desire for an answer does not ensure
that a reasonable answer can be extracted from a given body of data.
~ John Tukey
-----Oorspronkelijk bericht-----
Van: r-help-bounces@r-project.org [mailto:r-help-bounces@r-project.org] Namens
Craig O'Connell
Verzonden: maandag 28 april 2014 3:20
Aan: r-help@r-project.org
Onderwerp: [R] lme4 Error Help: “maxstephalfit…pwrssUpdate”
I am using a mixed model to assess the effects of various variables (i.e.
treatment, density, visibility) on bee behavior (e.g., avoidance frequency -
total avoidances per total visits; feeding frequency, and mating frequency).
Bee individuals is my random factor (n=63 different bees), whereas treatment
type, animal density, and air visibility are my fixed factors.
However, when I run my models, I immediately get an error that I cannot fix.
Here is a sample of my data:
Bee Treatment Visits Avoid Feeding Mating Density Visibility
1 C 5 0 5 0 5 4
2 C 4 0 3 0 5 4
3 C 3 0 3 0 5 4
...
63
1 PC 2 0 1 1 5 4
2 PC 3 0 0 3 5 4
3 PC 1 0 0 0 5 4
...
63
1 M 5 0 1 3 5 4
2 M 3 2 0 0 5 4
3 M 2 0 0 2 5 4
...
63One I create my .txt file, I being my coding in R by first loading lme4.
After that, my coding starts off as follows:
barrierdat = read.table("GLMMROW.txt", header=TRUE) barrierdat
barrierdat$Visibility = as.factor(barrierdat$Visibility);
barrierdat$Density = as.factor(barrierdat$Density);
p01.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee),
family=poisson,
data=egghead); # null model; p02.glmer =
glmer(Avoidance~offset(log(Visits))+(1|Bee)+Treatment, family=poisson,
data=egghead);
p03.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee)+Visibility,
family=poisson,
data=egghead);
p04.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee)+Density,
family=poisson,
data=egghead);However, upon immediately running my models
(e.g. p01.glmer), I receive the error:
Error: (maxstephalfit) PIRLS step-halvings failed to reduce deviance in
pwrssUpdate
Does anybody know what the issue is? I ran similar data several weeks ago and
had no issues. Any Suggestions on how to proceed?
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
* * * * * * * * * * * * * D I S C L A I M E R * * * * * * * * * * * * *
Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer en
binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is
door een geldig ondertekend document.
The views expressed in this message and any annex are purely those of the writer
and may not be regarded as stating an official position of INBO, as long as the
message is not confirmed by a duly signed document.
Thanks. I used the most current version of lme4 that is why I was a bit concerned. My data seems appropriate and with lme4 working last week on a very similar data set, I was left a bit confused. Since I only starting implementing this technique, does anybody have some pointers on what I should look for that may potentially cause some issues?> > -----Oorspronkelijk bericht----- > Van: r-help-bounces@r-project.org [mailto:r-help-bounces@r-project.org] Namens Craig O'Connell > Verzonden: maandag 28 april 2014 3:20 > Aan: r-help@r-project.org > Onderwerp: [R] lme4 Error Help: “maxstephalfit…pwrssUpdate” > > I am using a mixed model to assess the effects of various variables (i.e. treatment, density, visibility) on bee behavior (e.g., avoidance frequency - total avoidances per total visits; feeding frequency, and mating frequency). Bee individuals is my random factor (n=63 different bees), whereas treatment type, animal density, and air visibility are my fixed factors. > However, when I run my models, I immediately get an error that I cannot fix. Here is a sample of my data: > Bee Treatment Visits Avoid Feeding Mating Density Visibility > > 1 C 5 0 5 0 5 4 > 2 C 4 0 3 0 5 4 > 3 C 3 0 3 0 5 4 > ... > 63 > > 1 PC 2 0 1 1 5 4 > 2 PC 3 0 0 3 5 4 > 3 PC 1 0 0 0 5 4 > ... > 63 > > 1 M 5 0 1 3 5 4 > 2 M 3 2 0 0 5 4 > 3 M 2 0 0 2 5 4 > ... > 63One I create my .txt file, I being my coding in R by first loading lme4. After that, my coding starts off as follows: > barrierdat = read.table("GLMMROW.txt", header=TRUE) barrierdat barrierdat$Visibility = as.factor(barrierdat$Visibility); > barrierdat$Density = as.factor(barrierdat$Density); > > p01.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee), family=poisson, > data=egghead); # null model; p02.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee)+Treatment, family=poisson, > data=egghead); > p03.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee)+Visibility, family=poisson, > data=egghead); > p04.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee)+Density, family=poisson, > data=egghead);However, upon immediately running my models (e.g. p01.glmer), I receive the error: > Error: (maxstephalfit) PIRLS step-halvings failed to reduce deviance in pwrssUpdate > > Does anybody know what the issue is? I ran similar data several weeks ago and had no issues. Any Suggestions on how to proceed? > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > * * * * * * * * * * * * * D I S C L A I M E R * * * * * * * * * * * * * > Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is door een geldig ondertekend document. > The views expressed in this message and any annex are purely those of the writer and may not be regarded as stating an official position of INBO, as long as the message is not confirmed by a duly signed document.[[alternative HTML version deleted]]
Thanks. I used the most current version of lme4 that is why I was a bit concerned. My data seems appropriate and with lme4 working last week on a very similar data set, I was left a bit confused. Since I only starting implementing this technique, does anybody have some pointers on what I should look for that may potentially cause some issues?> > -----Oorspronkelijk bericht----- > Van: r-help-bounces@r-project.org [mailto:r-help-bounces@r-project.org] Namens Craig O'Connell > Verzonden: maandag 28 april 2014 3:20 > Aan: r-help@r-project.org > Onderwerp: [R] lme4 Error Help: “maxstephalfit…pwrssUpdate” > > I am using a mixed model to assess the effects of various variables (i.e. treatment, density, visibility) on bee behavior (e.g., avoidance frequency - total avoidances per total visits; feeding frequency, and mating frequency). Bee individuals is my random factor (n=63 different bees), whereas treatment type, animal density, and air visibility are my fixed factors. > However, when I run my models, I immediately get an error that I cannot fix. Here is a sample of my data: > Bee Treatment Visits Avoid Feeding Mating Density Visibility > > 1 C 5 0 5 0 5 4 > 2 C 4 0 3 0 5 4 > 3 C 3 0 3 0 5 4 > ... > 63 > > 1 PC 2 0 1 1 5 4 > 2 PC 3 0 0 3 5 4 > 3 PC 1 0 0 0 5 4 > ... > 63 > > 1 M 5 0 1 3 5 4 > 2 M 3 2 0 0 5 4 > 3 M 2 0 0 2 5 4 > ... > 63One I create my .txt file, I being my coding in R by first loading lme4. After that, my coding starts off as follows: > barrierdat = read.table("GLMMROW.txt", header=TRUE) barrierdat barrierdat$Visibility = as.factor(barrierdat$Visibility); > barrierdat$Density = as.factor(barrierdat$Density); > > p01.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee), family=poisson, > data=egghead); # null model; p02.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee)+Treatment, family=poisson, > data=egghead); > p03.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee)+Visibility, family=poisson, > data=egghead); > p04.glmer = glmer(Avoidance~offset(log(Visits))+(1|Bee)+Density, family=poisson, > data=egghead);However, upon immediately running my models (e.g. p01.glmer), I receive the error: > Error: (maxstephalfit) PIRLS step-halvings failed to reduce deviance in pwrssUpdate > > Does anybody know what the issue is? I ran similar data several weeks ago and had no issues. Any Suggestions on how to proceed? > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > * * * * * * * * * * * * * D I S C L A I M E R * * * * * * * * * * * * * > Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is door een geldig ondertekend document. > The views expressed in this message and any annex are purely those of the writer and may not be regarded as stating an official position of INBO, as long as the message is not confirmed by a duly signed document.[[alternative HTML version deleted]]