Logistic Regression in R
Budget: $10 – $30 USD
I am working in RStudio and need a clear, well-documented logistic regression model that I can reproduce and interpret confidently. The goal is to use predictive analytics to estimate the probability of a binary outcome from my data set. I will provide a cleaned CSV along with a brief data dictionary.
Here is what I expect:
• An R script (or RMarkdown) that imports the data, explores key predictors, builds the logistic regression, checks multicollinearity, and carries out goodness-of-fit diagnostics (AIC, ROC/AUC, confusion matrix).
• Concise comments explaining each step so I can tweak the code later.
• A short summary outlining significant predictors, odds ratios, and any recommended next steps.
Please rely only on base R or tidyverse and caret packages—no proprietary add-ins. If you see opportunities for feature engineering or cross-validation to improve performance, include them in the script. Deliver the final files and a brief walkthrough so I’m able to replicate the results on my machine.
Here is what I expect:
• An R script (or RMarkdown) that imports the data, explores key predictors, builds the logistic regression, checks multicollinearity, and carries out goodness-of-fit diagnostics (AIC, ROC/AUC, confusion matrix).
• Concise comments explaining each step so I can tweak the code later.
• A short summary outlining significant predictors, odds ratios, and any recommended next steps.
Please rely only on base R or tidyverse and caret packages—no proprietary add-ins. If you see opportunities for feature engineering or cross-validation to improve performance, include them in the script. Deliver the final files and a brief walkthrough so I’m able to replicate the results on my machine.