contrasts among simple effects

Dear James,

Please keep the mailing list in cc. Most likely someone else would have
told you that the errors are due to a syntax error. You want lme(HR ~
drug*ordered(time), random =~1|person, correlation =
corAR1(form=~time|person), data = heartRate)

Best regards,

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

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

2015-10-16 19:07 GMT+02:00 James Henson <jfhenson1 at gmail.com>:

Dear Thierry,

Thank you for the counsel. However, my perplexity persists.  Many
variations of adding 'corAR1(form = ~time|person)' return an error
message.  Some of these variations are below.

model2b <- lme(HR ~ drug*ordered(time), random =~1|person, correlation
=corAR1(, form=~1|person) =corAR1(, form=~time|person), data = heartRate)

Error: unexpected '=' in "model2b <- lme(HR ~ drug*ordered(time), random
=~1|person, correlation =corAR1(, form=~1|person) ="

model2b <- lme(HR ~ drug*ordered(time), random =~1|person, correlation

=corAR1(, form=~1|person) corAR1(, form=~time|person), data = heartRate)

Error: unexpected symbol in "model2b <- lme(HR ~ drug*ordered(time),
random =~1|person, correlation =corAR1(, form=~1|person) corAR1"



model2b <- lme(HR ~ drug*ordered(time), random =~1|person, correlation
=corAR1(, form=~1|person), =corAR1(, form=~time|person), data = heartRate)

Error: unexpected '=' in "model2b <- lme(HR ~ drug*ordered(time), random
=~1|person, correlation =corAR1(, form=~1|person), ="



model2b <- lme(HR ~ drug*ordered(time), random =~1|person, correlation
=corAR1(, form=~time|person), data = heartRate)

Error in structure(res, levels = lv, names = nm, class = "factor") :
'names' attribute [72] must be the same length as the vector [0]



model2b <- lme(HR ~ drug*ordered(time), random =~1|person, correlation
=corAR1(, form=~1|person, time|person), data = heartRate)

Error in time | person :  operations are possible only for numeric,
logical or complex types



model2b <- lme(HR ~ drug*ordered(time), random =~1|person, correlation
=corAR1(, form=~1|person, form=~time|person), data = heartRate)

Error in corAR1(, form = ~1 | person, form = ~time | person) :  formal
argument "form" matched by multiple actual arguments



model2b <- lme(HR ~ drug*ordered(time), random =~1|person, correlation
=corAR1(, form=~1|person), correlation= corAR1(, form=~time|person), data =
heartRate)

Error in lme(HR ~ drug * ordered(time), random = ~1 | person, correlation
= corAR1(,  :   formal argument "correlation" matched by multiple actual
arguments


Hopefully, you can help.

Books on my shelve show R examples from behavioral science.  Need a
cookbook with R examples from  biology/agriculture, but have not found one.


Best regards,

James F. Henson

Research Scientist

Southern University

Baton Rouge, USA

Wisdom is knowing what you don't know. ~ Socrates





On Fri, Oct 16, 2015 at 6:24 AM, Thierry Onkelinx <
thierry.onkelinx at inbo.be> wrote:

Dear James,

I think that you need to specify the order of the data as well.
corAR1(form = ~time|person). Otherwise the order of the observations as
present in the data is used.

Best regards,

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

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

2015-10-14 18:46 GMT+02:00 James Henson <jfhenson1 at gmail.com>:

Greetings R Community

Apologize for previously sending a csv file.

My goal is to make orthogonal contrasts among simple effects in
analysis of
repeated measures data.  The SAS publication, on page 1224, shows how to
make this type of contrasts in SAS.  But, my search of books about
repeated
measures analysis using R, and on-line has not yielded a methodology.
Hopefully, someone can direct me to a book or publication that will
show me
a methodology.

Statistical Analysis of Repeated Measures Data Using SAS Procedures


http://cslras.pbworks.com/f/littell_j_anim_sci_76_4_analysis_of_repeated_measures_using_sas.pdf



Attached is a txt data file (file name = heart_rate.txt).  My code for
the
repeated measures analysis is below.

library("nlme")

# with AR1 variance/covariance structure, with ordered statement

heartRate$time <- factor(heartRate$time)

model2a <- lme(HR ~ drug*ordered(time), random =~1|person, correlation
=corAR1(, form=~1|person), data = heartRate)

summary(model2a)

anova(model2a)

Making a new variable ?simple? that merges the variables drug and time
will
enable me to make orthogonal contrasts among the simple effects.  But,
when
using the variable ?simple? as the independent variable, the data will
no
longer be fitted to the AR1 variance/covariance structure.

Thanks.

Best regards,

James F.Henson