depression: Treatment for severe postnatal depression

depressionR Documentation

Treatment for severe postnatal depression

Description

These data arose from a study on the efficacy of oestrogen given transdermally for the treatment of severe postnatal depression. Women with major depression were randomly assigned to a placebo control group or an oestrogen patch group. Prior to the treatment all women were assessed by self-rated depressive symptoms on the Edinburgh Postnatal Depression Scale (EPDS). EPDS data were collected monthly for six months once treatment began. Higher EDPS scores are indicative of higher depression levels.

Usage

data(depression)

Format

A data frame with 427 rows and 5 variables:

subj

a numeric vector giving the identifier of each woman.

group

a factor giving the received treatment: "placebo" or "oestrogen".

visit

a numeric vector giving the number of months since the treatment began, where -1 indicates the pretreatment assessment of the EDPS.

dep

a numeric vector giving the value of the EDPS.

depressd

a numeric vector coded as 1 when the value of the EDPS is greater than or equal to 11 and coded as 0 in other cases.

Source

https://stats.oarc.ucla.edu/spss/library/spss-librarypanel-data-analysis-using-gee/

References

Gregoire A.J.P., Kumar R., Everitt B., Henderson A.F., Studd J.W.W. (1996) Transdermal oestrogen for treatment of severe postnatal depression, The Lancet 347:930-933.

Examples

data(depression)
dev.new()
boxplot(dep ~ visit, data=subset(depression,group=="placebo"), at=c(0:6) - 0.2,
        col="yellow", boxwex=0.3, xaxt="n", ylim=range(na.omit(depression$dep)),
        xlab="Months since the treatment began", ylab="EDPS")
boxplot(dep ~ visit, data=subset(depression,group=="oestrogen"), add=TRUE,
        at=c(0:6) + 0.2, col="blue", boxwex=0.3, xaxt="n")
axis(1, at=c(0:6), labels=c(-1,1:6))
legend("bottomleft", legend=c("placebo","oestrogen"), fill=c("yellow","blue"),
       title="Treatment", bty="n")


glmtoolbox documentation built on Sept. 11, 2024, 7:32 p.m.