panic2 {nparLD}

Panic disorder study II

Description

Measurements of the degree of illness on a P&A scale for a group of patients suffering from panic disorder with or without agoraphobia.

Usage

data(panic2)

Format

Longitudinal data of 37 patients with P&A scores taken on 5 occasions.

Details

A group of 37 patients with a panic disorder with/without agoraphobia was treated with anti-depressant imipramin over a period of eight weeks. The severity of the panic disorder was determined at five different occasions in increments of two weeks (0=baseline, 2=after two weeks, 4=after four weeks,...) using the new P&A scale (Bandelow, 1995, 1999), a discrete scale assigning to each patient a value between 0 and 52. Aim of this study was to determine whether a patient's improvement as measured by the P&A scale was different depending on whether or not the patient suffered from agoraphobia (w=with agoraphobia, wo=without agoraphobia).

References

Bandelow, B. (1995). Assessing the efficacy of treatments for panic disorder and agoraphobia, II. The Panic and Agoraphobia Scale. International Journal of Clinical Psychopharmacology 10, 73 2.

Bandelow, B. (1999). Panic and Agoraphobia Scale (PAS). Hogrefe & Huber, Goettingen.

Brunner, E., Domhof, S., and Langer, F. (2002). Nonparametric Analysis of Longitudinal Data in Factorial Experiments, Wiley, New York.

Brunner, E. and Langer, F. (1999). Nichtparametrische Analyse longitudinaler Daten, R. Oldenbourg Verlag, Munchen Wien.

Noguchi, K., Gel, Y.R., Brunner, E., and Konietschke, F. (2012). nparLD: An R Software Package for the Nonparametric Analysis of Longitudinal Data in Factorial Experiments. Journal of Statistical Software, 50(12), 1-23.

Examples

## Analysis using F1-LD-F1 design ##
data(panic2)
attach(panic2)
w.t<-c(1:5)
w.g<-c(1:2)
w.pat<-rbind(c(1:5), c(1:5))
ex.f1f1.2<-f1.ld.f1(y=resp, time=time, group=group, subject=subject, w.pat=w.pat, 
w.t=w.t, w.g=w.g, time.name="Week", group.name="Agoraphobia", description=FALSE)
# F1 LD F1 Model 
# ----------------------- 
# Check that the order of the time and group levels are correct.
# Time level:   0 2 4 6 8 
# Group level:   w wo 
# If the order is not correct, specify the correct order in time.order or 
# group.order.

## Wald-type statistic
ex.f1f1.2$Wald.test

#              	   Statistic df     p-value
#Agoraphobia        8.427367  1 3.696152e-03
#Week             119.793400  4 5.912722e-25
#Agoraphobia:Week  13.493440  4 9.100275e-03

## ANOVA-type statistic
ex.f1f1.2$ANOVA.test

#           	  Statistic       df     p-value
#Agoraphobia       8.427367 1.000000 3.696152e-03
#Week             32.089272 2.693506 7.109822e-19
#Agoraphobia:Week  1.751998 2.693506 1.599706e-01

## ANOVA-type statistic for the whole-plot factor
ex.f1f1.2$ANOVA.test.mod.Box

#            Statistic df1      df2     p-value
#Agoraphobia  8.427367   1 28.62587 0.007044246