# reliability

##### Reliability

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 critera: 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 to`FALSE`

.- .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.

##### 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 CI's are returned.

##### 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).

##### Functions

`calculateRhoC`

: Calculate the congeneric reliability`calculateRhoT`

: Calculate the tau-equivalent reliability

##### References

##### See Also

*Documentation reproduced from package cSEM, version 0.3.0, License: GPL-3*