eqMI.ncp: Obtain noncentrality parameter of a chisquare distribution

Description Usage Arguments Details Value References Examples

View source: R/eqMI.ncp.R

Description

Calculate the noncentrality parameter as well as the model missipecification epsilon_t given its lower-tail critical value.

Usage

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eqMI.ncp(T, df, N, m, alpha = 0.05)

Arguments

T

A chi-square statistic

df

Degrees of freedom

N

Total sample size of all groups

m

Number of groups

alpha

Significance level. Default at 0.05.

Details

This function is to compute the noncentrality parameter ncp, the model missipecification epsilon_t, and its corresponding RMSEA_t. With equivalence testing, the model missipecification is also the minimum tolerable size that a researcher needs to tolerate if one wishes to proceed with further restricted tests. The formula from Venables (1975) is used for obtaining the noncentrality parameter of a non-central chi-square distribution given its lower-tail critical value.

Value

The noncentrality parameter ncp, the minimum tolerable size epsilon_t, and RMSEA_t under equivalence testing.

References

Yuan, K. H., & Chan, W. (2016). Measurement invariance via multigroup SEM: Issues and solutions with chi-square-difference tests. Psychological methods, 21(3), 405-426.

Examples

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alpha <- .05
n_1 <- 200
n_2 <- 200
N <- n_1 + n_2
m <- 2
# A made-up likelihood-ratio statistic
T_ml <- 8.824
df <- 6
eqMI.ncp(T = T_ml, df = df, N = N, m = m, alpha = alpha)

gabriellajg/equaltestMI documentation built on May 27, 2018, 9:34 p.m.