
lmer Experts:

I am trying to use lmer to duplicate the results found in Joop Hox's  
book "Multilevel Analysis: technique and applications" 2002.  In  
chapter 6 of his book he shows an example of multilevel logistic  
regression for a meta-analysis of survey response rates.  The data are  
available in the file "metaresp.xls" at his website:

<http://www.geocities.com/joophox/mlbook/excelxls.zip>

The dataset includes the following variables of interest:

Individual level (Level 1) variables:
TELDUM	 = telephone questioning
MAILDUM  = mail questioning
RESPONSE = the outcome of interest, the study response rate
DENOM    = the number of people questioned

Study/group level (Level 2) variables:
SOURCE 	 = the study identifier
YEAR	 = year of study
SALIENCY = how salient the questionnaire was (0 to 2)
RESPISRR = the way the response rate was calculated


The null model (Table 6.2) proposed by Joop is easy to fit:

SUCCESS <- as.integer(RESPISRR*DENOM)
y  	<- cbind(SUCCESS, DENOM-SUCCESS)

f1 <- lmer(y ~ RESPISRR + (1 | SOURCE), family=binomial(link=logit))


Joop then adds a couple Level 1 variables (Table 6.3):

f2 <- lmer(y ~ RESPISRR + TELNUM + MAILDUM + (1 | SOURCE),  
family=binomial(link=logit))


He then says that these two Level 1 variables should be allowed to  
vary across studies (varying slopes).  When I try to fit what I  
believe to be the correct model, I get an error


f3 <- lmer(y ~ RESPISRR + TELNUM + MAILDUM + (TELNUM | SOURCE) +  
(MAILDUM | SOURCE)
	+ (1 | SOURCE), family=binomial(link=logit))

Error in mer_finalize(ans) : q = 240 > n = 105


Can anyone tell me what I am doing wrong here?  Thanks so much in  
advance.

Brant Inman
Duke University Medical Center

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