ci | R Documentation |
This function returns a (1-\alpha
)% confidence interval (CI) for a
well–defined nonlinear function of the coefficients in single–level and
multilevel structural equation models. The ci
function uses the Monte
Carlo (type="MC"
) and the asymptotic normal theory
(type="asymp"
) with the multivariate delta standard error
(Asymptotic–Delta) method (Sobel, 1982) to compute a CI. In addition, for
each of the methods, when a user specifies plot=TRUE
and
plotCI=TRUE
, a plot of the sampling distribution of the quantity of
interest in the quant
argument and an overlaid plot of the CI will be
produced. When type="all"
and plot=TRUE
, two overlaid plots of
the sampling distributions corresponding to each method will be produced;
when plotCI=TRUE
, then the overlaid plots of the CIs for both methods
will be displayed as well.
ci(
mu,
Sigma,
quant,
alpha = 0.05,
type = "MC",
plot = FALSE,
plotCI = FALSE,
n.mc = 1e+06,
H0 = FALSE,
mu0 = NULL,
Sigma0 = NULL,
...
)
mu |
(1) a vector of means (e.g., coefficient estimates) for the
normal random variables. A user can assign a name to each mean value, e.g.,
|
Sigma |
either a covariance matrix or a vector that stacks all the columns of the lower triangle variance–covariance matrix one underneath the other. |
quant |
quantity of interest, which is a nonlinear/linear function of
the model parameters. Argument |
alpha |
significance level for the CI. The default value is .05. |
type |
method used to compute a CI. It takes on the values |
plot |
when |
plotCI |
when |
n.mc |
Monte Carlo sample size. The default sample size is 1e+6. |
H0 |
False. If |
mu0 |
a vector of means (e.g., coefficient estimates) for the
normal random variables that satisfy the null hypothesis |
Sigma0 |
either a covariance matrix or a vector that stacks all
the columns of the lower triangle variance–covariance matrix one
underneath the other. If it is not provided, then |
... |
additional arguments. |
When type
is "MC"
or "asymp"
, ci
returns
a list that contains:
( |
a vector of lower and upper confidence limits, |
Estimate |
a point estimate of the quantity of interest, |
SE |
standard error of the quantity of interest, |
MC Error |
When |
When type="all"
, ci
returns a list of two
objects, each of which a list that contains the results produced by
each method as described above.
A shiny web application for Monte Carlo method of this function is available at https://amplab.shinyapps.io/MEDMC/
Davood Tofighi dtofighi@gmail.com
Tofighi, D. and MacKinnon, D. P. (2011). RMediation: An R package for mediation analysis confidence intervals. Behavior Research Methods, 43, 692–700. \Sexpr[results=rd]{tools:::Rd_expr_doi("doi:10.3758/s13428-011-0076-x")}
medci
RMediation-package
ci(
mu = c(b1 = 1, b2 = .7, b3 = .6, b4 = .45),
Sigma = c(.05, 0, 0, 0, .05, 0, 0, .03, 0, .03),
quant = ~ b1 * b2 * b3 * b4, type = "all", plot = TRUE, plotCI = TRUE
)
# An Example of Conservative Null Sampling Distribution
ci(c(b1 = .3, b2 = .4, b3 = .3), c(.01, 0, 0, .01, 0, .02),
quant = ~ b1 * b2 * b3, type = "mc", plot = TRUE, plotCI = TRUE,
H0 = TRUE, mu0 = c(b1 = .3, b2 = .4, b3 = 0)
)
# An Example of Less Conservative Null Sampling Distribution
ci(c(b1 = .3, b2 = .4, b3 = .3), c(.01, 0, 0, .01, 0, .02),
quant = ~ b1 * b2 * b3, type = "mc", plot = TRUE, plotCI = TRUE,
H0 = TRUE, mu0 = c(b1 = 0, b2 = .4, b3 = 0.1)
)
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