Data Upload & Auto-Profiling

Upload your dataset and the system automatically detects variable types, missingness, and structural risks.

Drop your CSV or Excel file here

or click to browse · .csv · .xlsx

trial_cohort_v3.csvuploaded

Rows

842

Columns

8

Event rate

12%

Events

101

Dataset Preview

First 8 rows · 842 total
idtreatment_groupagesexbaseline_scoresitecomorbidity_indexsurvival_90d
001A52M47.2S121
002B38F53.8S201
003A61M41.5S130
004B45F58.1S311
005A70M35.9S440
006B29F64.3S201
007A56M49.7S521
008B63F38.2S630

Auto-Profile Summary

Automatic
binary·survival_90d
categorical·treatment_groupsexsite
continuous·agebaseline_score
count·comorbidity_index
id·id

Missingness

id
treatment_group
age1.2%
sex
baseline_score3.6%
site
comorbidity_index
survival_90d

Risk Flags

LOW_EVENTS_PER_VARIABLEWith 101 events and 7 predictors (including an 8-level site variable), events per variable (EPV) may be borderline for complex models. The system will calculate the exact events-per-parameter (EPP) ratio once you confirm variable encodings in step 2.
MISSINGNESS_DETECTED2 predictors have missing values (age 1.2%, baseline_score 3.6%). Multiple imputation is available as a sensitivity analysis option.

Variable Distributions

Automatic
agecontinuous
baseline_scorecontinuous
comorbidity_indexcount
treatment_groupcategorical
sexcategorical
sitecategorical
survival_90dbinary

Pairwise Correlations

Automatic

Pearson correlations across continuous and count variables. Strong correlations may indicate collinearity.

age
baseline_score
comorbidity
age
-0.24
0.38
baseline_score
-0.24
-0.31
comorbidity
0.38
-0.31