ttdetect: Finding a detectable odds Ratio with a given power

In TrendInTrend: Odds Ratio Estimation and Power Calculation for the Trend in Trend Model

Description

Monte Carlo power calculation for a trend-in-trend design.

Usage

ttdetect(N, time, G, cstat, alpha_t, beta_0, power, nrep, OR.vec)

Arguments

N	Sample Size.
time	Number of time points.
G	Number of CPE strata.
cstat	Value of the c-statistic.
alpha_t	A scaler that qunatifies the trend in exposure prevalence.
beta_0	Intercept of the outcome model.
power	A given power.
nrep	Number of Monte Carlo replicates.
OR.vec	A vector of odds Ratios.

Value

Power	A vector of calculated powers for a given OR.vec
OR.vec	A vector of odds Ratios
DetectDifference	A detectable difference for a given power value

References

Ertefaie, A., Small, D., Ji, X., Leonard, C., Hennessy, S. (2018). Statistical Power for Trend-in-trend Design. Epidemiology 29(3), e21.

Examples

set.seed(123)
ttdetect(N=10000,time=10,G=10,cstat=0.75,alpha_t= 0.4,beta_0=-4.3,
        power=0.80,nrep=50, OR.vec=c(1.9,2.0,2.1,2.2))
 

TrendInTrend documentation built on March 13, 2020, 2:54 a.m.