Publications by Mark Bounthavong
Two-part model - Application with cost data using R
Introduction Motivating example Two-part model Conclusion Acknowledgements Work in progress Cost as a dependent variable: Application of the two-part model Mark Bounthavong 30 April 2023 Introduction Modeling cost in a sample is problematic because of the large amount of subjects with zero costs and the long right-tail distribution. Alt...
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Interpreting Regression Models
Interpreting regression models Multivariable regression models Conclusions Work in progress Interpreting Regression Models Mark Bounthavong 2023-02-27 Interpreting regression models In my course, we have introduce three types of regression models: linear, logistic, and survival. Each of these are used in specific ...
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MEPS Tutorial 3 - Applying weights
Introduction Types of weights Loading the data Perform descriptive analysis Conclusions Acknowledgements MEPS Tutorial 3 - Applying weights Mark Bounthavong 2023-01-13 Introduction The Medical Expenditure Panel Survey (MEPS) is based on a complex survey design. Hence, it is necessary to apply survey weights to generate esti...
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Stata tutorial - Add 95% Confidence Intervals to Two-way Line Plot
Introduction Stata is a statistical software the is used to perform statistical analysis. It is one of my favorite statistical software, and I use it for many of my projects. Stata also has a powerful graphic editing tool that allows for a full range of customization. However, I like to keep all of these in the code so that I can have a conv...
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MEPS Tutorial 1 - Loading data into R
Introduction MEPS Data Load MEPS data into R Conclusions Acknowledgements MEPS Tutorial 1 - Loading Data into R Mark Bounthavong 2022-12-24 Introduction The Agency for Healthcare Research and Quality (AHRQ) Medical Expenditure Panel Survey (MEPS) is a set of data on U.S. households about their healthcare expend...
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MEPS Tutorial 2 - Mergining Data into R
Introduction Load MEPS data Merge MEPS data Reduce dataframe to a few variables Add an indicator for a specific ICD10 diagnostic code Collapse dataframe to a single unique patient Conclusions Acknowledgements MEPS Tutorial 2 - Merging data Mark Bounthavong 2023-01-06 Introduction We want...
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Decision Tree Model in R Tutorial
Introduction We make decisions everyday from getting up in the morning to figuring out what we want to have for dinner. In most cases, we have a good idea of what we like or want based on previous experiences. For example, you might prefer to have ice cream for dinner because you like it. But what if you also believe that having ice cream is not ...
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Forest plots in R
Forest plots Forest plots are useful when summarizing the invidivual impact of studies on the pooled end points for meta analysis or illustrating the influence of coefficients in a regression model. More importantly, they visualize the direction and magnitude of the associations between the individual studies or coefficients on the outcomes. The ...
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Confounding and Interaction
R tutorial using epitools: Confounding and Effect Modification Mark Bounthavong 9/26/2021 Updated on 01/28/2022 ⊕This tutorial is located on RPubs. ⊕The entire R Markdown code is located on my GitHub page Installing and using epitools This tutorial will center around using the R package epitools to understand confounding and interaction in ep...
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Logistic Regression in R - Part 2 (Goodness of fit)
Introduction In a previous article, we discuss how to construct a logistic regression in R (see previous article). However, we did not discuss how to assess whether the logistic regression fit our data well. In this article, we’ll go over some goodness of fit tests to help determine whether the logistic regression model does a good job of fitti...
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