mda.biber functions

boxplot_mda

The boxplot_mda() function combines scaled vectors of the relevant factor loadings and boxplots of diminesion scores.

Description

The boxplot_mda() function combines scaled vectors of the relevant factor loadings and boxplots of diminesion scores.

Usage

boxplot_mda(mda_data, n_factor = 1)

Arguments

Argument

Description

mda_data

An mda data.frame produced by the mda_loadings() function.

n_factor

The factor to be plotted.

Value

A combined plot of scaled vectors and boxplots.

heatmap_mda

The heatmap_mda() function combines a stick plot with a heat map of the relevant factor loadings.

Description

The heatmap_mda() function combines a stick plot with a heat map of the relevant factor loadings.

Usage

heatmap_mda(mda_data, n_factor = 1)

Arguments

Argument

Description

mda_data

An mda data.frame produced by the mda_loadings() function.

n_factor

The factor to be plotted.

Value

A combined stick plot and heat map.

mda_loadings

Multi-Dimensional Analysis is a statistical procedure developed Biber and is commonly used in descriptions of language as it varies by genre, register, and task. The procedure is a specific application factor analysis, which is used as the basis for calculating a ‘dimension score’ for each text.

Description

The function mda_loadings() returns a data.frame of dimension scores with the means for each category and the factor loadings accessible as attributes. Calculating MDA requires a data.frame containing a column with a categorical variable (formatted as a factor) and more than 2 continuous, numeric variables.

Usage

mda_loadings(obs_by_group, n_factors, cor_min = 0.2, threshold = 0.35)

Arguments

Argument

Description

obs_by_group

A data.frame containing 1 categorical (factor) variable and continuous (numeric) variables.

n_factors

The number of factors to be calculated in the factor analysis.

cor_min

The correlation threshold for including variables in the factor analysis.

threshold

A value indicating the threshold at which variables should be included in dimension score calculations (the default is .35).

Value

An mda data structure containing scores, means by group, and factor loadings

screeplot_mda

A wrapper for the nScree function included in the nFactors package.

Description

A wrapper for the nScree function included in the nFactors package.

Usage

screeplot_mda(obs_by_group, cor_min = 0.2)

Arguments

Argument

Description

obs_by_group

A data.frame containing 1 categorical (factor) variable and continuous (numeric) variables.

cor_min

The correlation threshold for including variables in the factor analysis.

Value

A scree plot.

stickplot_mda

A simple function for producing the stick plots that are common in visualizing the location of category means along a given dimension.

Description

A simple function for producing the stick plots that are common in visualizing the location of category means along a given dimension.

Usage

stickplot_mda(mda_data, n_factor = 1)

Arguments

Argument

Description

mda_data

An mda data.frame produced by the mda_loadings() function.

n_factor

The factor to be plotted.

Value

A stick plot showing category means long a positve/negative cline.