Compute several reliability estimates. See the Reliability section of the cSEM website for details.
Usage
calculateRhoC(
.object = NULL,
.model_implied = TRUE,
.only_common_factors = TRUE,
.weighted = FALSE
)
calculateRhoT(
.object = NULL,
.alpha = 0.05,
.closed_form_ci = FALSE,
.only_common_factors = TRUE,
.output_type = c("vector", "data.frame"),
.weighted = FALSE,
...
)
Arguments
- .object
An R object of class cSEMResults resulting from a call to
csem()
.- .model_implied
Logical. Should weights be scaled using the model-implied indicator correlation matrix? Defaults to
TRUE
.- .only_common_factors
Logical. Should only concepts modeled as common factors be included when calculating one of the following quality criteria: AVE, the Fornell-Larcker criterion, HTMT, and all reliability estimates. Defaults to
TRUE
.- .weighted
Logical. Should estimation be based on a score that uses the weights of the weight approach used to obtain
.object
?. Defaults toFALSE
.- .alpha
An integer or a numeric vector of significance levels. Defaults to
0.05
.- .closed_form_ci
Logical. Should a closed-form confidence interval be computed? Defaults to
FALSE
.- .output_type
Character string. The type of output. One of "vector" or "data.frame". Defaults to "vector".
- ...
Ignored.
Value
For calculateRhoC()
and calculateRhoT()
(if .output_type = "vector"
)
a named numeric vector containing the reliability estimates.
If .output_type = "data.frame"
calculateRhoT()
returns a data.frame
with as many rows as there are
constructs modeled as common factors in the model (unless
.only_common_factors = FALSE
in which case the number of rows equals the
total number of constructs in the model). The first column contains the name of the construct.
The second column the reliability estimate.
If .closed_form_ci = TRUE
the remaining columns contain lower and upper bounds
for the (1 - .alpha
) confidence interval(s).
Details
Since reliability is defined with respect to a classical true score measurement
model only concepts modeled as common factors are considered by default.
For concepts modeled as composites reliability may be estimated by setting
.only_common_factors = FALSE
, however, it is unclear how to
interpret reliability in this case.
Reliability is traditionally based on a test score (proxy) based on unit weights.
To compute congeneric and tau-equivalent reliability based on a score that
uses the weights of the weight approach used to obtain .object
use .weighted = TRUE
instead.
For the tau-equivalent reliability ("rho_T
" or "cronbachs_alpha
") a closed-form
confidence interval may be computed Trinchera2018cSEM by setting
.closed_form_ci = TRUE
(default is FALSE
). If .alpha
is a vector
several CIs are returned.
Functions
calculateRhoC()
: Calculate the congeneric reliabilitycalculateRhoT()
: Calculate the tau-equivalent reliability