scaleDiagnosis provides a number of diagnostics for a scale (an aggregative measure consisting of several items).

```
scaleDiagnosis(
data = NULL,
items = NULL,
plotSize = 180,
sizeMultiplier = 1,
axisLabels = "none",
scaleReliability.ci = FALSE,
conf.level = 0.95,
normalHist = TRUE,
poly = TRUE,
digits = 3,
headingLevel = 3,
scaleName = NULL,
...
)
# S3 method for scaleDiagnosis
print(x, digits = x$digits, ...)
scaleDiagnosis_partial(
x,
headingLevel = x$input$headingLevel,
quiet = TRUE,
echoPartial = FALSE,
partialFile = NULL,
...
)
# S3 method for scaleDiagnosis
knit_print(
x,
headingLevel = x$headingLevel,
quiet = TRUE,
echoPartial = FALSE,
partialFile = NULL,
...
)
```

- data
A dataframe containing the items in the scale. All variables in this dataframe will be used if items is NULL.

- items
If not NULL, this should be a character vector with the names of the variables in the dataframe that represent items in the scale.

- plotSize
Size of the final plot in millimeters.

- sizeMultiplier
Allows more flexible control over the size of the plot elements

- axisLabels
Passed to ggpairs function to set axisLabels.

- scaleReliability.ci
TRUE or FALSE: whether to compute confidence intervals for Cronbach's Alpha and Omega (uses bootstrapping function in MBESS, takes a while).

- conf.level
Confidence of confidence intervals for reliability estimates (if requested with scaleReliability.ci).

- normalHist
Whether to use the default ggpairs histogram on the diagonal of the scattermatrix, or whether to use the

`normalHist()`

version.- poly
Whether to also request the estimates based on the polychoric correlation matrix when calling

`scaleStructure()`

.- digits
The number of digits to pass to the

`print`

method for the descriptives dataframe.- headingLevel
The level of the heading (number of hash characters to insert before the heading, to be rendered as headings of that level in Markdown).

- scaleName
Optionally, a name for the scale to print as heading for the results.

- ...
Additional arguments for

`scaleDiagnosis()`

are passed on to`scatterMatrix()`

, and additional arguments for the`print`

method are passed to the default`print`

method.- x
The object to print.

- quiet
Whether to be chatty (

`FALSE`

) or quiet (`TRUE`

).- echoPartial
Whether to show the code in the partial (

`TRUE`

) or hide it (`FALSE`

).- partialFile
The file with the Rmd partial (if you want to overwrite the default).

An object with the input and several output variables. Most notably:

- scaleReliability
The results of scaleReliability.

- pca
A Principal Components Analysis

- fa
A Factor Analysis

- describe
Decriptive statistics about the items

- scatterMatrix
A scattermatrix with histograms on the diagonal and correlation coefficients in the upper right half.

Function to generate an object with several useful statistics and a plot to assess how the elements (usually items) in a scale relate to each other, such as Cronbach's Alpha, omega, the Greatest Lower Bound, a factor analysis, and a correlation matrix.

```
### Note: the 'not run' is simply because running takes a lot of time,
### but these examples are all safe to run!
if (FALSE) {
### This will prompt the user to select an SPSS file
scaleDiagnosis();
### Generate a datafile to use
exampleData <- data.frame(item1=rnorm(100));
exampleData$item2 <- exampleData$item1+rnorm(100);
exampleData$item3 <- exampleData$item1+rnorm(100);
exampleData$item4 <- exampleData$item2+rnorm(100);
exampleData$item5 <- exampleData$item2+rnorm(100);
### Use a selection of two variables
scaleDiagnosis(data=exampleData, items=c('item2', 'item4'));
### Use all items
scaleDiagnosis(data=exampleData);
}
```