sim.CC.data.ExE: Simulates case and controls

Description Usage Arguments Value Author(s)

Description

Generates affected and non-affected subjects until the set sample size is achieved.

Usage

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sim.CC.data.ExE(n = NULL, ncases = NULL, ncontrols = NULL,
  max.sample.size = NULL, pheno.prev = NULL, e1.model = NULL,
  e1.prev = NULL, e1.mean = NULL, e1.sd = NULL, e1.low.lim = NULL,
  e1.up.lim = NULL, e1.OR = NULL, e2.model = NULL, e2.prev = NULL,
  e2.mean = NULL, e2.sd = NULL, e2.low.lim = NULL, e2.up.lim = NULL,
  e2.OR = NULL, i.OR = NULL, b.OR = NULL, ph.error = NULL)

Arguments

n

Number of observations to generate per iteration

ncases

Number of cases to simulate

ncontrols

Number of controls to simulate

max.sample.size

Maximum number of observations allowed

pheno.prev

Prevalence of the binary outcome

e1.model

Model of the 1st environmental exposure

e1.prev

Prevelance of the 1st environmental exposure

e1.mean

Mean of the 1st environmental exposure

e1.sd

Standard deviation of the 1st environmental exposure

e1.low.lim

Lower limit of the 1st environmental exposure

e1.up.lim

Upper limit of the 1st environmental exposure

e1.OR

Odds ratios of the 1st environmental exposure

e2.model

Model of the 2nd environmental exposure

e2.prev

Prevelance of the 2nd environmental exposure

e2.mean

Mean of the 2nd environmental exposure

e2.sd

Standard deviation of the 2nd environmental exposure

e2.low.lim

Lower limit of the 2nd environmental exposure

e2.up.lim

Upper limit of the 2nd environmental exposure

e2.OR

Odds ratios of the 2nd environmental exposure

i.OR

Odds ration of the interaction

b.OR

Baseline odds ratio for subject on 95 percent population centile versus 5 percentile. This parameter reflects the heterogeneity in disease risk arising from determinates that have not been measured or have not been included in the model.

ph.error

misclassification rates: 1-sensitivity and 1-specificity

Value

A matrix

Author(s)

Gaye A.


agaye/ESPRESSO.ExE documentation built on May 10, 2019, 7:30 a.m.