anomo (version 1.2.2)

mcci: Compute Monte Carlo Confidence Intervals

Description

Compute Monte Carlo confidence intervals (MCCIs) for the difference and equivalence tests.

Usage

mcci(
  d = NULL,
  se = NULL,
  mediation = FALSE,
  n.mcci = 10000,
  sig.level = 0.05,
  sig.adjusted = TRUE,
  two.tailed = TRUE,
  seed = 123,
  eq.bd = NULL,
  xlim = NULL,
  xlab = NULL,
  ylab = NULL,
  dashed.lines = TRUE,
  verbose = TRUE
)

Value

The results of moderation analysis and equivalence tests using the MCCI method. It will also provide a plot for the MCCIs.

Arguments

d

The estimated effect(s), it has a length of one, two, and four. (1) When the length is one, it is an estimated main or moderation effect, the MCCI compute the CI for this estimate; (2) When the length is two, they represent two estimated effects. These two estimated effects are main or moderation effects when mediation is FALSE, the MCCI compute the CI for the difference of the two estimates; These two estimated effects are the treatment-mediator and mediator-outcome path estimates for a mediation effect when mediation is TRUE; the MCCI compute the CI for the mediation effects. (3) When the length is four, they represent the mediation effects in two studies in the following order: the treatment-mediator and mediator-outcome path estimates in studies (groups) 1 and 2.

se

The corresponding standard error(s) for parameter d.

mediation

Logical; d and se represent parameters for a mediation effect if TRUE; d and se represent parameters for a main or moderation effect if FALSE; default value is FALSE.

n.mcci

The number of draws for the MCCI method. Default is 10,000.

sig.level

The significance level. Default is .05.

sig.adjusted

Logical; use Bonferroni correction (i.e., dividing the original significance level by the number of tests) if TRUE, otherwise not; default value is TRUE.

two.tailed

Logical of two tailed test for difference test. Default is TRUE.

seed

Random seed for replication, default is 123.

eq.bd

The limit of the equivalence bounds for an equivalence test. Default is the MCCI for the equivalence test. It can be specified in the arguments as eq.bd = a positive number or eq.bd = c(lower bound #, upper bound #).

xlim

The limits set for the x-axis in the plot. Default is the MCCI for the difference test. It can be specified in the arguments as xlim = c(lower #, higher #).

xlab

The label for the x-axis in the plot. Default is "Differences in Effects".

ylab

The label for the y-axis in the plot. Default is NULL.

dashed.lines

Logical of whether dashed lines of equivalence bounds and zero should be added in the plot. Default is TRUE.

verbose

Logical; print the process if TRUE, otherwise not; default value is TRUE.

Examples

   library(anomo)
# 1. Compute MCCIs for main or moderation effects-----
   # 1.1. Compute MCCIs for one main or moderation effect from one study
   myci <- mcci(d = .1, se = .02); myci$out
   # 1.2 Compute MCCIs for differences in two main (or moderation) effects
   myci <- mcci(d = c(0.1, 0.15), se = c(.02, 0.01)); myci$out
   # 1.3 Compute MCCIs for differences across five main (or moderation) effects
   myci <- mcci(d = c(0.10, 0.15, 0.20, 0.25, 0.30),
                se = c(0.01, 0.01, 0.02, 0.02, 0.03))
   myci$out

# 2. Compute MCCIs for mediation effects
   # 2.1. Compute MCCIs for an estimated mediation effect
   myci <- mcci(d = c(.1, 0.15), se = c(.02, 0.01), mediation = TRUE)
   myci$out
   # 2.1. Compute MCCIs for differences in two mediation effects
   myci <- mcci(d = c(0.30, 0.50, 0.33, 0.55),
                se = c(0.02, 0.01, 0.02, 0.03), mediation = TRUE)
                myci$out
# 3. Explicitly specify other parameters
   myci <- mcci(d = .05, se = .02, eq.bd = 0.1) # equivalence bounds
   myci <- mcci(d = .05, se = .02, xlim = c(-0.15, 0.15)) # Range of x-axis