Manualizing Factor Analysis of Likert Scale Data

Applying Multigroup Confirmatory Factor Models for Continuous Outcomes to Likert Scale Data Complicates Meaningful Group Comparisons

Large Scale Experiments Data Analysis for Estimation of Hydrodynamic Force Coefficients Part 1: Time Domain Analysis

This paper describes various time-domain methods useful for analyzing the experimental data obtained from a circular cylinder force in terms of both wave and current for estimation of the drag and inertia coefficients applicable to the Morison’s equation. An additional approach, weighted least squares method is also introduced. A set of data obtained from experiments on heavily roughened circul...

A Comparison of Imputation Strategies for Ordinal Missing Data on Likert Scale Variables.

This article compares a variety of imputation strategies for ordinal missing data on Likert scale variables (number of categories = 2, 3, 5, or 7) in recovering reliability coefficients, mean scale scores, and regression coefficients of predicting one scale score from another. The examined strategies include imputing using normal data models with naïve rounding/without rounding, using latent va...

An Empirical Study on the Transformation of Likert-scale Data to Numerical Scores

The application of statistical methods to data analysis requires that the data set concerned should follow some particular assumptions. For example, AVOVA assumes that the response variable is normally distributed within groups, and the variances in the different groups are identical. However such assumptions are generally not observed by data collected through Likert Scales. This paper present...

Use of Laplacian Projection Technique for Summarizing Likert Scale Annotations

Summarizing Likert scale ratings from human annotators is an important step for collecting human judgments. In this project we study a novel, graph theoretic method for this purpose. We also analyze a few interesting properties for this approach using real annotation datasets.