Using Parallel Feature Analysis (PFA), NXG Logic Explorer can simultaneously perform ANOVA, Kruskal-Wallis tests, and Bartlett's homogeneity of variance tests for multiple features, including multiway contingency table analysis with chi-squared tests of association for multiple categorical variables across the same two groups. Thus, many parametric and non-parametric K-sample tests for continuous and categorical features are performed, which typically takes less than a minute. Any time Bartlett's test is significant for a continuously-scaled feature, Welch ANOVA will be performed.
The output involves a single table for which fonts and colors can be changed, based on the needs of the user -- using a pasteable html or graphic image.
All of the above tests can be employed simultaneously for 20-30 features in less than minute.
Using Parallel Feature Analysis (PFA), NXG Logic Explorer can simultaneously perform ANOVA, Kruskal-Wallis tests, and Bartlett's homogeneity of variance tests for multiple features, including multiway contingency table analysis with chi-squared tests of association for multiple categorical variables across the same two groups. Thus, many parametric and non-parametric K-sample tests for continuous and categorical features are performed, which typically takes less than a minute. Any time Bartlett's test is significant for a continuously-scaled feature, Welch ANOVA will be performed.
The output involves a single table for which fonts and colors can be changed, based on the needs of the user -- using a pasteable html or graphic image.
All of the above tests can be employed simultaneously for 20-30 features in less than minute.
Step 1: Start Explorer, and input the Retinol dataset (5 seconds).
Step 1: Start Explorer, and input the Retinol dataset (5 seconds).
Step 2: Select independence tests, unpaired 2-sample (2 seconds).
Step 2: Select independence tests, unpaired 2-sample (2 seconds).
Step 3: A 3-group ANOVA (Kruskal-Wallis) set of tests along with chi-squared tests for SEX and SMOKING can be quickly run by simply selecting the 3-group VITUSE (vitamin use) variable as the grouping variable, with all remaining variables as the test variables (5 seconds).
Step 3: A 3-group ANOVA (Kruskal-Wallis) set of tests along with chi-squared tests for SEX and SMOKING can be quickly run by simply selecting the 3-group VITUSE (vitamin use) variable as the grouping variable, with all remaining variables as the test variables (5 seconds).
Using Parallel Feature Analysis (PFA), NXG Logic Explorer can simultaneously perform ANOVA, Kruskal-Wallis tests, and Bartlett's homogeneity of variance tests for multiple features, including multiway contingency table analysis with chi-squared tests of association for multiple categorical variables across the same two groups. Thus, many parametric and non-parametric K-sample tests for continuous and categorical features are performed, which typically takes less than a minute. Any time Bartlett's test is significant for a continuously-scaled feature, Welch ANOVA will be performed.
The output involves a single table for which fonts and colors can be changed, based on the needs of the user -- using a pasteable html or graphic image.
All of the above tests can be employed simultaneously for 20-30 features in less than minute.
Step 4: Select the Grouped analysis icon and view the output table (5 seconds). Note that Welch ANOVA is used when Bartlett's test is significant, due to heteroscedasticity (unequal variances). This can be noticed by a change in the denominator d.f. of the F-ratio test - shown in the table. Again, you can see the asymptotic p-value for the chi-squared tests along with the Fisher exact test (10,000) iterations.
Step 4: Select the Grouped analysis icon and view the output table (5 seconds). Note that Welch ANOVA is used when Bartlett's test is significant, due to heteroscedasticity (unequal variances). This can be noticed by a change in the denominator d.f. of the F-ratio test - shown in the table. Again, you can see the asymptotic p-value for the chi-squared tests along with the Fisher exact test (10,000) iterations.
Step 1: Start Explorer, and input the Retinol dataset (5 seconds).
Chi-squared tests are run the same time parametric and non-parametric tests are run on the continuous variables.
Chi-squared tests are run the same time parametric and non-parametric tests are run on the continuous variables.
Step 2: Select independence tests, unpaired 2-sample (2 seconds).
In summary, the total time required to run the 4 steps was less than a minute, and the results included a dozen variables and dozens of tests, while all the necessary tests concerning equality of variances were ran behind the scenes, with Welch tests employed if heteroscedasticity was present. The chi-squared tests were also performed on the categorical variables which happened to be included in the 3-group tests.
The above runs are ideal for generating demographic tables for intervention studies, case-control, cohort and prospective, and baseline variables for randomized clinical trials and longitudinal studies with k-treatment groups. Group labels can be easily input using the label editor or by input of text files containing categorical group labels.
The analyses presented above are also available in the free Standard edition of Explorer. Once you become accustomed to the time-savings offered by using Explorer, you will begin to realize how much time you have wasted with your current software. We also use Explorer whenever possible, since we can't afford to waste time and lose the productivity associated with use of so many other platforms.
In summary, the total time required to run the 4 steps was less than a minute, and the results included a dozen variables and dozens of tests, while all the necessary tests concerning equality of variances were ran behind the scenes, with Welch tests employed if heteroscedasticity was present. The chi-squared tests were also performed on the categorical variables which happened to be included in the 3-group tests.
The above runs are ideal for generating demographic tables for intervention studies, case-control, cohort and prospective, and baseline variables for randomized clinical trials and longitudinal studies with k-treatment groups. Group labels can be easily input using the label editor or by input of text files containing categorical group labels.
The analyses presented above are also available in the free Standard edition of Explorer. Once you become accustomed to the time-savings offered by using Explorer, you will begin to realize how much time you have wasted with your current software. We also use Explorer whenever possible, since we can't afford to waste time and lose the productivity associated with use of so many other platforms.
Step 3: A 3-group ANOVA (Kruskal-Wallis) set of tests along with chi-squared tests for SEX and SMOKING can be quickly run by simply selecting the 3-group VITUSE (vitamin use) variable as the grouping variable, with all remaining variables as the test variables (5 seconds).
Step 4: Select the Grouped analysis icon and view the output table (5 seconds). Note that Welch ANOVA is used when Bartlett's test is significant, due to heteroscedasticity (unequal variances).
This can be noticed by a change in the denominator d.f. of the F-ratio test - shown in the table. Again, you can see the asymptotic p-value for the chi-squared tests along with the Fisher exact test (10,000) iterations.
Chi-squared tests are run the same time parametric and non-parametric tests are run on the continuous variables.
In summary, the total time required to run the 4 steps was less than a minute, and the results included a dozen variables and dozens of tests, while all the necessary tests concerning equality of variances were ran behind the scenes, with Welch tests employed if heteroscedasticity was present. The chi-squared tests were also performed on the categorical variables which happened to be included in the 3-group tests.
The above runs are ideal for generating demographic tables for intervention studies, case-control, cohort and prospective, and baseline variables for randomized clinical trials and longitudinal studies with k-treatment groups. Group labels can be easily input using the label editor or by input of text files containing categorical group labels.
The analyses presented above are also available in the free Standard edition of Explorer. Once you become accustomed to the time-savings offered by using Explorer, you will begin to realize how much time you have wasted with your current software. We also use Explorer whenever possible, since we can't afford to waste time and lose the productivity associated with use of so many other platforms.
