Title

predict -- Obtaining predictions after drmeta command for dose-response meta-analysis

Syntax for predict

predict stubname [ , statistic ]

statistic

Main
xb linear prediction for the fixed portion of the model only; the default

xbs linear prediction using study-specific coefficient vector

fitted fitted values, fixed-portion linear prediction plus
contributions based on predicted random effects

reffects predicted BLUPs of random effects

Description

The predict command after drmeta creates a new variable containing the requested predictions using
study-specific reference values.

Options

xb linear prediction for the fixed portion of the model only.

xbs linear prediction using study-specific coefficient vector estimated using generalized least squares; the default.

fitted fitted values, fixed-portion linear prediction plus contributions based on predicted random effects.

reffects predicted BLUPs of random effects.

Examples

* Read data about alcohol consumption and colorectal cancer risk (Orsini et al. AJE 1992)

use http://www.stats4life.se/data/ex_alcohol_crc.dta, clear

* Model 1. One-stage random-effects dose-response model assuming a linear trend

drmeta logrr dose , data(peryears cases) id(study) type(type) se(se) reml

* Prediction 1. Store the predicted contrasts using the GLS estimates obtained within each study

predict fit_xbs, xbs

* Prediction 2. Store the predicted contrasts using the estimated fixed-effects

predict fit_xb, xb

* Prediction 3. Store the predicted contrasts using the estimated fixed-effects plus the random-effects

predict fit_fitted, fitted

* Prediction 4. Store the predicted BLUPs of random-effects

predict fit_blup, reffect

* Examine predicted values

`"list study dose logrr fit_xb fit_xbs fit_fitted , sepby(study)"'

* Graphical comparison of dose-response curves estimated separately within each study (xbs) and with random-effects model (fitted)

`"twoway (scatter fit_xbs dose, sort c(ascending) lc(red)) (line fit_fitted dose, sort c(ascending) lc(blue)) , by(study, legend(off))"'

* Model 2. One-stage random-effects dose-response model using restricted cubic splines

mkspline doses = dose, nk(3) cubic
drmeta logrr doses1 doses2 , data(peryears cases) id(study) type(type) se(se) reml

* Prediction 1. Store the predicted contrasts using the GLS estimates obtained within each study

predict fit2_xbs, xbs

* Prediction 2. Store the predicted contrasts using the estimated fixed-effects

predict fit2_fitted, fitted

* Graphical comparison of dose-response curves estimated separately within each study (xbs) and with random-effects model (fitted)

`"twoway (line fit2_xbs dose, sort lc(red)) (line fit2_fitted dose, sort lc(blue)) , by(study, legend(off))"'

Author

Nicola Orsini, Biostatistics Team,
Department of Public Health Sciences, Karolinska Institutet, Sweden

Support

http://www.stats4life.se

nicola.orsini@ki.se

Help: drmeta