ci.rmsea
(Package: MBESS) :
Confidence interval for the population root mean square error of approximation
Confidence interval for the population root mean square error of approximation (RMSEA).
● Data Source:
CranContrib
● Keywords: design
● Alias: ci.rmsea
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conf.limits.ncf
(Package: MBESS) :
Confidence limits for noncentral F parameters
Function to determine the noncentral parameter that leads to the observed F-value, so that a confidence interval around the population F-value can be conducted. Used for forming confidence intervals around noncentral parameters (given the monotonic relationship between the F-value and the noncentral value).
● Data Source:
CranContrib
● Keywords: design, multivariate, regression
● Alias: conf.limits.ncf
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This function implements the upsilon effect size statistic for general mediation from Lachowicz, Preacher, & Kelley (submitted).
● Data Source:
CranContrib
● Keywords: design
● Alias: upsilon
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ss.aipe.sem.path.sensitiv
(Package: MBESS) :
a priori Monte Carlo simulation for sample size planning for SEM targeted effects
Conduct a priori Monte Carlo simulation to empirically study the effects of (mis)specifications of input information on the calculated sample size. Random data are generated from the true covariance matrix but fit to the proposed model, whereas sample size is calculated based on the input covariance matrix and proposed model.
● Data Source:
CranContrib
● Keywords: design, multivariate
● Alias: ss.aipe.sem.path.sensitiv
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A function for the sequential estimation of the standardized mean difference with minimum risk. The function implements the ideas of Chattopadhyay and Kelley (submitted, Psychological Methods), which considers study cost and accuracy of the estimated standardized mean difference simultaniously. This is important to specify that mr.smd.R was developed under the assumption of normally distributed data with equal sample size and equal cost of sampling per observation for each group.
● Data Source:
CranContrib
● Keywords: design, htest, misc
● Alias: mr.smd
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ss.aipe.c.ancova
(Package: MBESS) :
Sample size planning for a contrast in randomized ANCOVA from the Accuracy in Parameter Estimation (AIPE) perspective
A function to calculate the appropriate sample size per group for the (unstandardized) contrast, in one-covariate randomized ANCOVA, so that the width of the confidence interval is sufficiently narrow.
● Data Source:
CranContrib
● Keywords: design
● Alias: ss.aipe.c.ancova
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ci.pvaf
(Package: MBESS) :
Confidence Interval for the Proportion of Variance Accounted for (in the dependent variable by knowing the levels of the factor)
Function to obtain the exact confidence limits for the proportion of variance of the dependent variable accounted for by knowing the levels of the factor (or the grouping factor in a single factor design) group status in a fixed factor analysis of variance.
● Data Source:
CranContrib
● Keywords: design
● Alias: ci.pvaf
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ss.aipe.cv
(Package: MBESS) :
Sample size planning for the coefficient of variation given the goal of Accuracy in Parameter Estimation approach to sample
Determines the necessary sample size so that the expected confidence interval width for the coefficient of variation will be sufficiently narrow, optionally with a desired degree of certainty that the interval will not be wider than desired.
● Data Source:
CranContrib
● Keywords: design, htest
● Alias: ss.aipe.cv
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ci.reliability
(Package: MBESS) :
Confidence Interval for a Reliability Coefficient
A function to calculate the point estimate and confidence interval for a reliability coefficient (alpha, omega, and variations thereof). Please see the many options; the defaults may not be best for your situtaion. BKelley and Pornprasertmanit (in press), for example, recomend bias corrected and accelerated bootstrap("interval.type=bca" with categorical omega (type=hierarchical).
● Data Source:
CranContrib
● Keywords: htest, misc
● Alias: ci.reliability
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ci.R
(Package: MBESS) :
Confidence interval for the multiple correlation coefficient
A function to obtain the confidence interval for the population multiple correlation coefficient when predictors are random (the default) or fixed.
● Data Source:
CranContrib
● Keywords: design, regression
● Alias: ci.R
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