RMediation: pprodnormal – R documentation

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pprodnormal

Percentile for the Distribution of Product of Two Normal Variables

Description

Generates percentiles (100 based quantiles) for the distribution of product of two normal random variables and the mediated effect

Usage

pprodnormal(q, mu.x, mu.y, se.x=1, se.y=1, rho = 0, lower.tail=TRUE,
type="dop", n.mc=1e5)

Arguments

`q`	quantile or value of the product
`mu.x`	mean of x
`mu.y`	mean of y
`se.x`	standard error (deviation) of x
`se.y`	standard error (deviation) of y
`rho`	correlation between x and y, where -1 < `rho` < 1. The default value is 0.
`lower.tail`	logical; if `TRUE` (default), the probability is P[XY < q]; otherwise, P[XY > q]
`type`	method used to compute P[XY < q]*. It takes on the values `"dop"` (default), `"MC"`, or `"all"`.
`n.mc`	when `type="MC"`, `n.mc` determines the sample size for the Monte Carlo method. The default sample size is 1E5.

Details

This function returns the percentile (probability) and the associated error for the distribution of product of mediated effect (two normal random variables). To obtain a percentile using a specific method, the argument type should be specified. The default method is type="dop", which is based on the method described by Meeker and Escobar (1994) to evaluate the CDF of the distribution of product of two normal random variables. type="MC" uses the Monte Carlo approach (Tofighi & MacKinnon, 2011). type="all" prints percentiles using all three options. For the method type="dop", the error is the modulus of absolute error for the numerical integration (for more information see Meeker and Escobar, 1994). For type="MC", the error refers to the Monte Carlo error.

Value

An object of the type list that contains the following values:

`p`	probability (percentile) corresponding to quantile `q`
`error`	estimate of the absolute error

Author(s)

Davood Tofighi dtofighi@unm.edu and David P. MacKinnon davidpm@asu.edu

References

MacKinnon, D. P., Fritz, M. S., Williams, J., and Lockwood, C. M. (2007). Distribution of the product confidence limits for the indirect effect: Program PRODCLIN. Behavior Research Methods, 39, 384–389.

Meeker, W. and Escobar, L. (1994). An algorithm to compute the CDF of the product of two normal random variables. Communications in Statistics: Simulation and Computation, 23, 271–280.

Tofighi, D. and MacKinnon, D. P. (2011). RMediation: An R package for mediation analysis confidence intervals. Behavior Research Methods, 43, 692–700. doi:10.3758/s13428-011-0076-x

Examples

pprodnormal(q=0, mu.x=.5, mu.y=.3, se.x=1, se.y=1, rho= 0, type="all")

RMediation

Mediation Analysis Confidence Intervals

v1.1.4

GPL-2

Authors

Davood Tofighi <dtofighi@unm.com> and David P. MacKinnon <davidpm@asu.edu>

Initial release

2016-3-12