R: Pretest-posttest RCT for quantitative observations with...

prepost.test {MESS} | R Documentation

## Pretest-posttest RCT for quantitative observations with possible missing values

### Description

In a typical pretest-posttest RCT, subjects are randomized to two treatments, and response is measured at baseline, prior to intervention with the randomized treatment (pretest), and at prespecified follow-up time (posttest). Interest focuses on the effect of treatments on the change between mean baseline and follow-up response. Missing posttest response for some subjects is routine, and disregarding missing cases can lead to invalid inference.

### Usage

    prepost.test(baseline, post, treatment, conf.level = 0.95, delta = "estimate")

### Arguments

`baseline` | A vector of quantitative baseline measurements
`post` | A vector of quantitative post-test measurements with same length as baseline. May contain missing values
`treatment` | A vector of 0s and 1s corresponding to treatment indicator. 1 = treated, Same length as baseline
`conf.level` | confidence level of the interval
`delta` | A numeric between 0 and 1 OR the string "estimate" (the default). The proportion of observation treated.

### Author(s)

Claus Ekstrom ekstrom@sund.ku.dk

### References

Marie Davidian, Anastasios A. Tsiatis and Selene Leon (2005). "Semiparametric Estimation of Treatment Effect in a Pretest-Posttest Study with Missing Data". Statistical Science 20, 261-301.

### See Also

`chisq.test`

### Examples

    # From Altman
    expo = c(rep(1,9),rep(0,7))
    bp1w = c(137,120,141,137,140,144,134,123,142,139,134,136,151,147,137,149)
    bp_base = c(147,129,158,164,134,155,151,141,153,133,129,152,161,154,141,156)
    diff = bp1w-bp_base
    prepost.test(bp_base, bp1w, expo)

[Package MESS version 0.5.9 Index]