get.critical.results.GxG: Summarizes the main results

In agaye/ESPRESSO.GxG: Power Analysis and Sample Size Calculation for a gene-gene interaction model

Description

Gets the number of cases and controls or subjects and the empirical and theoretical power under each model and prints a summary on the screen

Usage

get.critical.results.GxG(scenario = NULL, pheno.model = NULL,
  geno1.model = NULL, geno2.model = NULL, sample.sizes.required = NULL,
  empirical.power = NULL, modelled.power = NULL, mean.beta = NULL)

Arguments

scenario	Scenario number
pheno.model	Type of the outcome; 0 for binary and 2 for continuous
geno1.model	Genetic model of the 1st SNP; 0 for binary and 1 for additive
geno2.model	Genetic model of the 1st SNP; 0 for binary and 1 for additive
sample.sizes.required	Number of cases and controls or number of subjects required to achieve the desired power
empirical.power	Estimated empirical power
modelled.power	Calculated theoretical power
mean.beta	Mean beta value of each of the determinants

Value

A table containing the following items: gene1.model Model of the first genetic determinant gene2.model Model of the second genetic determinant number.of.cases.required Number of cases required to achieve the desired power under binary outcome model number.of.controls.required Number of controls required to achieve the desired power under binary outcome model number.of.subjects.required Number of subjects required to achieve the desired power under a quantatative outcome model empirical.power Estimated empirical power under each model modelled.power Power achieved under each model with specified sample size estimated.OR Estimated odds-ratios due to shrinkage toward the null resulting from misclassification estimated.effect Estitmated effect size if the outocme is continuous

Author(s)

Gaye A.

agaye/ESPRESSO.GxG documentation built on May 10, 2019, 7:31 a.m.