ivmodel (version 1.9.1)

IVsize: Calculating minimum sample size for achieving a certain power

Description

IVsize calculates the minimum sample size needed for achieving a certain power in one of the following tests: two stage least square estimates; Anderson-Rubin (1949) test; Sensitivity analysis.

Usage

IVsize(ivmodel, power, alpha = 0.05, beta = NULL, type = "TSLS", 
       deltarange = NULL, delta = NULL)

Value

minimum sample size needed for achieving a certain power

Arguments

ivmodel

ivmodel object.

power

The power threshold to achieve.

alpha

The significance level for hypothesis testing. Default is 0.05.

beta

True causal effect minus null hypothesis causal effect. If missing, will use the beta calculated from the input ivmodel object.

type

Determines which test will be used for power calculation. "TSLS" for two stage least square estimates; "AR" for Anderson-Rubin test; "ARsens" for sensitivity analysis.

deltarange

Range of sensitivity allowance. A numeric vector of length 2. If missing, will use the deltarange from the input ivmodel object.

delta

True value of sensitivity parameter when calculating the power. Usually take delta = 0 for the favorable situation or delta = NULL for unknown delta.

Author

Yang Jiang, Hyunseung Kang, Dylan Small

Details

IVsize calculates the minimum sample size needed for achieving a certain power for one of the following tests: two stage least square estimates; Anderson-Rubin (1949) test; Sensitivity analysis. The related value of parameters will be inferred from the input of ivmodel object.

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.
Anderson, T.W. and Rubin, H. (1949). Estimation of the parameters of a single equation in a complete system of stochastic equations. Annals of Mathematical Statistics, 20, 46-63.
ang, X., Jiang, Y., Small, D. and Zhang, N (2017), Sensitivity analysis and power for instrumental variable studies, (under review of Biometrics).

See Also

See also ivmodel for details on the instrumental variables model. See also TSLS.size, AR.size, ARsens.size for calculation details.

Examples

data(card.data)
Y=card.data[,"lwage"]
D=card.data[,"educ"]
Z=card.data[,"nearc4"]
Xname=c("exper", "expersq", "black", "south", "smsa", "reg661", 
        "reg662", "reg663", "reg664", "reg665", "reg666", "reg667", 
		"reg668", "smsa66")
X=card.data[,Xname]
card.model = ivmodel(Y=Y,D=D,Z=Z,X=X, deltarange=c(-0.01, 0.01))

IVsize(card.model, power=0.8)
IVsize(card.model, power=0.8, type="AR")
IVsize(card.model, power=0.8, type="ARsens", deltarange=c(-0.01, 0.01))