mixor (version 1.0.4)

schizophrenia: National Institute of Mental Health Schizophrenia Collaborative Study

Description

In the NIMH Schizophrenia Collaborative Study, patients were randomized to receive one of four medications, either placebo or one of three different anti-psychotic drugs. The protocol indicated subjects were to then be evaluated at weeks 0, 1, 3, 6 to assess severity of illness; additionally some measurements were made at weeks 2, 4, and 5.

Usage

data(schizophrenia)

Format

A data frame with 1603 observations on the following 9 variables.

id

a numeric vector indicating the unique patient identifier

imps79

a numeric vector from item 79 on the Inpatient Multidimensional Psychiatric Scale indicating severity of illness. The scores were applied to be interpreted as follows: 1 = normal, not ill at all; 2 = borderline mentally ill; 3 = mildly ill; 4 = moderately ill; 5 = markedly ill; 6 = severly ill; 7 = among the most extremely ill

imps79b

a binary version of imps79

imps79o

an ordinally scaled version of imps79

int

a numeric vector of ones; used in stand-alone package to indicate intercept

TxDrug

a numeric vector indicating treatment with drug (1) or placebo (0)

Week

a numeric vector indicating time, in weeks

SqrtWeek

the square root of the Week variable

TxSWeek

a variable representing the TxDrug x Week interaction

References

Hedeker D. and Gibbons R.D. (1996) A computer program for mixed-effects ordinal regression analysis. Computer Methods and Programs in Biomedicine 49, 157-176. Hedeker D and Gibbons R.D. (2006) Longitudinal Data Analysis, Wiley, Hoboken, New Jesery.

Examples

# NOT RUN {
library("mixor")
data("schizophrenia")
### Random intercept
SCHIZO1.fit<-mixor(imps79o ~ TxDrug + SqrtWeek + TxSWeek, data=schizophrenia, 
     id=id, link="probit")
summary(SCHIZO1.fit)
### Random intercept and slope	
SCHIZO2.fit<-mixor(imps79o ~ TxDrug + SqrtWeek + TxSWeek, data=schizophrenia, 
     id=id, which.random.slope=2, link="probit")
summary(SCHIZO2.fit)
# random intercept and trend with independent random effects; using logit link
SCHIZO3.fit<-mixor(imps79o ~ TxDrug + SqrtWeek + TxSWeek, data=schizophrenia, 
     id=id, which.random.slope=2, indep.re=TRUE, link="logit")
summary(SCHIZO3.fit)
# }