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I have a dependent variable: rtln (log transformed reaction time) and 3 predictors: choicenum (ranging from 1 to 6), ifrelevant (0 and 1), and condition (0 and 1), and I have a variable with subject IDs.

I would like to estimate a model where choicenum is nested within subjects  . I use the following notation:

lmer(rtln~choicenum + ifrelevant + condition + (1|subject/choicenum), data=myData)

for some reason this estimates 5 fixed effects for choicenum.

Here's the output: http://dl.dropbox.com/u/22681355/output.tiff

Here's the dataset: http://dl.dropbox.com/u/22681355/data.csv

Here's the stata output of what I'd like to get: http://dl.dropbox.com/u/22681355/output.pdf

I have a dependent variable: rtln (log transformed reaction time) and 3 predictors: choicenum (ranging from 1 to 6), ifrelevant (0 and 1), and condition (0 and 1), and I have a variable with subject IDs.

I would like to estimate a model where choicenum is nested within subjects. I use the following notation:

lmer(rtln~choicenum + ifrelevant + condition 
 + (1|subject/choicenum),    data=myData)

for some reason this estimates 5 fixed effects for choicenum.

• Here's the output: http://dl.dropbox.com/u/22681355/output.tiff
• Here's the dataset: http://dl.dropbox.com/u/22681355/data.csv
• Here's the stata output of what I'd like to get: http://dl.dropbox.com/u/22681355/output.pdf

I have a dependent variable: rtln (log transformed reaction time)

3 predictors: choicenum (ranging from 1 to 6) ifrelevant (0 and 1) condition (0 and 1)

and I have a variable with subject IDs.

I would like to estimate a model where choicenum are nested within subjects . I use the following notation:

lmer(rtln~choicenum + ifrelevant + condition + (1|subject/choicenum)

for some reason this estimates 5 fixed effects for choicenum.

Here's the output: http://dl.dropbox.com/u/22681355/output.tiff

Here's the dataset: http://dl.dropbox.com/u/22681355/data.csv

Here's the stata output of what I'd like to get: http://dl.dropbox.com/u/22681355/output.pdf

I have a dependent variable: rtln (log transformed reaction time) and 3 predictors: choicenum (ranging from 1 to 6), ifrelevant (0 and 1), and condition (0 and 1), and I have a variable with subject IDs.

I would like to estimate a model where choicenum is nested within subjects . I use the following notation:

lmer(rtln~choicenum + ifrelevant + condition + (1|subject/choicenum), data=myData)

for some reason this estimates 5 fixed effects for choicenum.

Here's the output: http://dl.dropbox.com/u/22681355/output.tiff

Here's the dataset: http://dl.dropbox.com/u/22681355/data.csv

Here's the stata output of what I'd like to get: http://dl.dropbox.com/u/22681355/output.pdf

I have a dependent variable: rtln (log transformed reaction time)

3 predictors: choicenum (ranging from 1 to 6) ifrelevant (0 and 1) condition (0 and 1)

and I have a variable with subject IDs.

I would like to estimate a model where choicenum are nested within subjects . I use the following notation:

lmer(rtln~choicenum + ifrelevant + condition + (1|subject/choicenum)

for some reason this estimates 5 fixed effects for choicenum.

Here's the output: http://dl.dropbox.com/u/22681355/output.tiff

Here's the dataset: http://dl.dropbox.com/u/22681355/data.csv

Here's the stata output of what I'd like to get: http://dl.dropbox.com/u/22681355/output.docx

I have a dependent variable: rtln (log transformed reaction time)

3 predictors: choicenum (ranging from 1 to 6) ifrelevant (0 and 1) condition (0 and 1)

and I have a variable with subject IDs.

I would like to estimate a model where choicenum are nested within subjects . I use the following notation:

lmer(rtln~choicenum + ifrelevant + condition + (1|subject/choicenum)

for some reason this estimates 5 fixed effects for choicenum.

Here's the output: http://dl.dropbox.com/u/22681355/output.tiff

Here's the dataset: http://dl.dropbox.com/u/22681355/data.csv

Here's the stata output of what I'd like to get: http://dl.dropbox.com/u/22681355/output.pdf