logitr - Logit Models w/Preference & WTP Space Utility Parameterizations
Fast estimation of multinomial (MNL) and mixed logit (MXL) models in R. Models can be estimated using "Preference" space or "Willingness-to-pay" (WTP) space utility parameterizations. Weighted models can also be estimated. An option is available to run a parallelized multistart optimization loop with random starting points in each iteration, which is useful for non-convex problems like MXL models or models with WTP space utility parameterizations. The main optimization loop uses the 'nloptr' package to minimize the negative log-likelihood function. Additional functions are available for computing and comparing WTP from both preference space and WTP space models and for predicting expected choices and choice probabilities for sets of alternatives based on an estimated model. Mixed logit models can include uncorrelated or correlated heterogeneity covariances and are estimated using maximum simulated likelihood based on the algorithms in Train (2009) <doi:10.1017/CBO9780511805271>. More details can be found in Helveston (2023) <doi:10.18637/jss.v105.i10>.
Last updated 21 days ago
log-likelihoodlogitlogit-modelmixed-logitmlogitmultinomial-regressionmxlmxl-modelspreference-spacepreferenceswillingness-to-paywtp
8.80 score 42 stars 1 packages 119 scripts 1.9k downloadssurveydown - Markdown-Based Surveys Using 'Quarto' and 'shiny'
Generate surveys using markdown and R code chunks. Surveys are composed of two files: a survey.qmd 'Quarto' file defining the survey content (pages, questions, etc), and an app.R file defining a 'shiny' app with global settings (libraries, database configuration, etc.) and server configuration options (e.g., conditional skipping / display, etc.). Survey data collected from respondents is stored in a 'PostgreSQL' database. Features include controls for conditional skip logic (skip to a page based on an answer to a question), conditional display logic (display a question based on an answer to a question), a customizable progress bar, and a wide variety of question types, including multiple choice (single choice and multiple choices), select, text, numeric, multiple choice buttons, text area, and dates. Because the surveys render into a 'shiny' app, designers can also leverage the reactive capabilities of 'shiny' to create dynamic and interactive surveys.
Last updated 2 hours ago
markdownquartoshinyshiny-appsshiny-rsupabasesurveysurveys
8.70 score 63 stars 91 scripts 412 downloads