DP_projections_HILS_SWLS_100
                        Data for plotting a Dot Product Projection
                        Plot.
Language_based_assessment_data_3_100
                        Example text and numeric data.
Language_based_assessment_data_8
                        Text and numeric data for 10 participants.
PC_projections_satisfactionwords_40
                        Example data for plotting a Principle Component
                        Projection Plot.
centrality_data_harmony
                        Example data for plotting a Semantic Centrality
                        Plot.
embeddings_from_huggingface2
                        Word embeddings from textEmbedLayersOutput
                        function
textCentrality          Compute cosine semantic similarity score
                        between single words' word embeddings and the
                        aggregated word embedding of all words.
textCentralityPlot      Plot words according to cosine semantic
                        similarity to the aggregated word embedding.
textEmbed               Extract layers and aggregate them to word
                        embeddings, for all character variables in a
                        given dataframe.
textEmbedLayerAggregation
                        Select and aggregate layers of hidden states to
                        form a word embeddings.
textEmbedLayersOutput   Extract layers of hidden states (word
                        embeddings) for all character variables in a
                        given dataframe.
textEmbedStatic         Applies word embeddings from a given
                        decontextualized static space (such as from
                        Latent Semantic Analyses) to all character
                        variables
textPCA                 Compute 2 PCA dimensions of the word embeddings
                        for individual words.
textPCAPlot             Plot words according to 2-D plot from 2 PCA
                        components.
textPlot                Plot words from textProjection() or
                        textWordPrediction().
textPredict             Predict scores or classification from, e.g.,
                        textTrain.
textPredictTest         Significance testing correlations If only y1 is
                        provided a t-test is computed, between the
                        absolute error from yhat1-y1 and yhat2-y1.
textProjection          Compute Supervised Dimension Projection and
                        related variables for plotting words.
textProjectionPlot      Plot words according to Supervised Dimension
                        Projection.
textSimilarity          Compute the cosine semantic similarity between
                        two text variables.
textSimilarityNorm      Compute the semantic similarity between a text
                        variable and a word norm (i.e., a text
                        represented by one word embedding that
                        represent a construct).
textSimilarityTest      Test whether there is a significant difference
                        in meaning between two sets of texts (i.e.,
                        between their word embeddings).
textTrain               Train word embeddings to a numeric (ridge
                        regression) or categorical (random forest)
                        variable.
textTrainLists          Individually trains word embeddings from
                        several text variables to several numeric or
                        categorical variables. It is possible to have
                        word embeddings from one text variable and
                        several numeric/categprical variables; or vice
                        verse, word embeddings from several text
                        variables to one numeric/categorical variable.
                        It is not possible to mix numeric and
                        categorical variables.
textTrainRandomForest   Train word embeddings to a categorical variable
                        using random forrest.
textTrainRegression     Train word embeddings to a numeric variable.
textWordPrediction      Compute predictions based on single words for
                        plotting words. The word embeddings of single
                        words are trained to predict the mean value
                        associated with that word. P-values does NOT
                        work yet.
textrpp_initialize      Initialize text required python packages
textrpp_install         Install text required python packages in conda
                        or virtualenv environment
textrpp_uninstall       Uninstall textrpp conda environment
word_embeddings_4       Word embeddings for 4 text variables for 40
                        participants
