ivmodel (version 1.9.1)

TSLS.size: Sample Size Calculator for the Power of Asymptotic T-test

Description

TSLS.size computes the minimum sample size required for achieving certain power of asymptotic t-test of TSLS estimator.

Usage

TSLS.size(power, beta, rho_ZD, sigmau, sigmaDsq, alpha = 0.05)

Value

Minimum sample size required for achieving certain power of asymptotic t-test of TSLS estimator.

Arguments

power

The desired power over a constant.

beta

True causal effect minus null hypothesis causal effect.

rho_ZD

Correlation between the IV Z and the exposure D.

sigmau

Standard deviation of potential outcome under control. (structural error for y)

sigmaDsq

The variance of the exposure D.

alpha

Significance level.

Author

Yang Jiang, Hyunseung Kang, and Dylan Small

Details

The calculation is based on inverting the power formula given in Freeman (2013).

References

Freeman G, Cowling BJ, Schooling CM (2013). Power and Sample Size Calculations for Mendelian Randomization Studies Using One Genetic Instrument. International journal of epidemiology, 42(4), 1157-1163.

See Also

See also ivmodel for details on the instrumental variables model.

Examples

# Assume we performed an asymptotic t-test of TSLS estimator in a study 
# with one IV (l=1) and the only one exogenous variable is the intercept 
# (k=1). We want to calculate the minimum sample size needed for this 
# test to have an at least 0.8 power.

# Suppose the null hypothesis causal effect is 0 and the true causal 
# effect is 1 (beta=1-0=1).
# The correlation between the IV and exposure is .5 (rho_ZD= .5).
# The standard deviation of potential outcome is 1(sigmau= 1). 
# The variance of the exposure is 1 (sigmaDsq=1).
# The significance level for the study is alpha = .05.

### minimum sample size required for aysmptotic t-test
TSLS.size(power=.8, beta=1, rho_ZD=.5, sigmau=1, sigmaDsq=1, alpha =.05)