getScore: Get data frame for the function riskPredict

In riskPredictClustData: Assessing Risk Predictions for Clustered Data

Description

Get data frame for the function riskPredict.

Usage

getScore(fmla, cidVar, subuidVar, statusVar, datFrame, mycorstr = "exchangeable",
  verbose = FALSE)

Arguments

fmla	A formula object for the function gee
cidVar	character. Phenotype variable name for cluster id
subuidVar	character. Phenotype variable name for unit id
statusVar	character. Phenotype variable name for progression status
datFrame	A data frame with at least 3 columns corresponding to cid (indicated by cidVar), subuid (indicated by subuidVar), status (indicated by statusID). cid indicates cluster id; subuid indicates unit ID within a cluster; status=1 indicates an eye is progressed; status=0 indicates an eye is not progressed.
mycorstr	character. indicates correlation structure. see the manual for the function gee in the R library gee
verbose	logical. indicating if summary of gee results should be printed out.

Value

A list with two elements: frame and gee.obj. frame is a data frame with at least 4 columns: cid, subuid, status, and score. cid indicates cluster id; subuid indicates unit ID within a cluster; status=1 indicates an eye is progressed; status=0 indicates an eye is not progressed; score represents the risk score.

gee.obj is the object returned by gee function.

Author(s)

Bernard Rosner <[e-mail]>, Weiliang Qiu <[e-mail]>, Meiling Ting Lee <[e-mail]>

References

Rosner B, Qiu W, and Lee MLT. Assessing Discrimination of Risk Prediction Rules in a Clustered Data Setting. Lifetime Data Anal. 2013 Apr; 19(2): 242-256.

Examples

set.seed(1234567)
datFrame = genSimDataGLMEM(nSubj = 30, beta0 = -6, sd.beta0i = 1.58, 
                          beta1 = 1.58, beta2 = -3.95, beta3 = 3.15, beta4 = 2.06,
                          beta5 = 0.51, beta6 = 1.47, beta7 = 3.11, 
                          p.smkcur = 0.08, p.inieye31 = 0.44, p.inieye32 = 0.42,
                          p.inieye41 = 0.12, p.inieye42 = 0.11, sd.lncalorc = 0.33)

print(dim(datFrame))
print(datFrame[1:2,])

tt1 = getScore(fmla = prog~smkcur+lncalorc+inieye3+inieye4+factor(rtotfat), 
  cidVar = "cid", subuidVar = "subuid", statusVar = "prog", 
  datFrame = datFrame, mycorstr = "exchangeable",
  verbose = FALSE)
myframe1=tt1$frame

gee.obj=tt1$gee.obj
print(summary(gee.obj))

print(dim(myframe1))
print(myframe1[1:3,])

riskPredictClustData documentation built on May 1, 2019, 6:34 p.m.