Your English writing platform
Discover LudwigSuggestions(4)
Exact(1)
We compared pre-admission characteristics, expressed as bivariate categories, using the χ test.
Similar(59)
For this model, the variable 'average hours per week' was collapsed to full-time and less than full-time workload (36 or more hours per week, <36 hours per week) because of the relative homogeneity in odds ratios across the categories used in the bivariate analyses.
We performed bivariate analyses using the chi-square test for nominal categories and the t-test for continuous variables to narrow the list of potential predictor variables.
We model the distribution of this bivariate binary endpoint using the bivariate probit model.
Categorical variables were described in the univariate and bivariate analysis using the overall number of cases (n) and the percentage of each category.
Statistical analysis included bivariate correlations using the Pearson product-moment coefficient correlation.
Bivariate analysis was conducted using the summative scores for each knowledge sub-category (general knowledge, medical eligibility knowledge, personal characteristic eligibility knowledge) and their cumulative score (overall knowledge).
Bivariate analyses were performed using the Fisher exact test.
Bivariate analysis was done using the Chi Square test.
Bivariate associations were tested using the Pearson chi-squared test.
Bivariate comparisons were evaluated using the chi-square test.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com