LOADING RAISINS
RAISINS-BINARY LOGISTIC REGRESSION ANALYSIS
Discover R A I S I N S (R & AI Solutions in INferential Statistics) - Your ultimate tool for mastering Binary Logistic Regression Analysis! Effortlessly upload your data and unlock instant, polished tables tailored for your research. Dive deeper with stunning visualization plots that reveal hidden data patterns, and benefit from automated interpretations. Transform complex statistical analyses into clear, actionable insights with ease!
Hey! Before proceeding, you can freely explore the app using our built-in datasets. You will love it!.
Ensure your subscription is complete before proceeding with Get Started.
Need any assistance or statistical support? Our team will be happy to arrange a free online meeting to guide you through the app and clarify your questions. RAISINS is designed to be simple-just upload your data and click Run.
Binary Logistic Regression Analysis
Please authenticate
Developed by
Team RAISINS, STATOBERRY LLP
Author: Chief Statistician
© All rights reserved to STATOBERRY LLP
Influence & Outlier Diagnostics
This table screens each observation for three distinct kinds of unusual behaviour:
A flag is a signpost, not a verdict: investigate flagged rows for data-entry errors, but do not delete an observation merely because it is flagged - a genuine extreme case can be the most informative observation.
- Outlier - the model predicts this observation poorly (a large standardized deviance residual); its observed outcome is far from its predicted probability. Flagged as Potential outlier (|standardized residual| > 2) or Extreme outlier (> 3).
- High leverage - the observation sits far from the others in the predictor (X) space, giving it unusual pull on the fit, even if it is well predicted. Flagged when leverage > 2p/n.
- Influential - removing this observation would visibly change the fitted coefficients (and odds ratios). It usually combines high leverage with a large residual, and is flagged when Cook's distance > 4/n.
A flag is a signpost, not a verdict: investigate flagged rows for data-entry errors, but do not delete an observation merely because it is flagged - a genuine extreme case can be the most informative observation.
Loading...
Download Diagnostics (CSV)
Pick a plot using the icon buttons below. Click the settings button ( ⚙ ) in the top-left corner of the plot to explore the extensive customization options, and download your plot in PNG, JPEG, TIFF, PDF or SVG.
Probability Curve
Odds Ratio
Importance
Residual Plot
Deviance Histogram
Calibration
Probability Distribution
ROC Curve
Confusion Matrix
CSV Data File Creator for Binary Logistic Regression Analysis
This is a user-friendly platform where you can generate CSV files for logistic analysis.
Enter the number of variables and observations in the sidebar panel. Upon submission, a table will appear in the main panel, where you can enter or paste numeric data.
You can copy numeric data from Excel and paste using Ctrl+V (non-numeric values will be ignored).
After entering data, download the CSV file and upload it in the analysis tab for logistic analysis.
This tool simplifies data entry and manipulation for efficient analysis.
RAISINS AI ENGINE
RAISINS Assistant . Enter to send . Shift+Enter for new line
