Sentence examples for mean comparison tests from inspiring English sources

Simple mean comparison tests were performed to compare fig/wasp size between subsections/genera involved in strict association with their partners and subsections/genera involved in multiple associations.

In addition, a one-way repeated measures analysis of variance with a two-tailed post-hoc Tukey mean comparison tests were performed on the change Mania Rating Scale scores from baseline.

Second, their analysis used mean comparison tests to compare usage on the basis of five farm and farmer demographic drivers, while we use multivariate analysis (logit) to analyze usage with 16 drivers, including farm, farmer demographic, and regional variables.

Mean comparison tests (t tests) were conducted by omitting one cluster dummy variable at a time and evaluating the significance of the coefficients on the other dummy variables by examining the t-statistics associated with each estimated coefficient.

Combining the datasets was necessary in order to achieve the necessary sample size for mean comparison tests to be meaningful.

2. Mean comparison tests for quantitative variables and comparison of proportions for qualitative data, among independent variables to check the comparability of the groups.

In addition, a one-way repeated measures analysis of variance with a two-tailed post hoc Tukey mean comparison test were performed in the change from baseline for HAM-D scores in each group.

In addition, a one-way repeated measures analysis of variance with a two-tailed post-hoc Tukey mean comparison test were performed on the change in Teacher and Parent ADHD Rating Scale scores from baseline.

Comparisons of the socio-economic profiles of households in which the indigents resided and of certain basic needs such as income, access to healthcare or to food (measure of vulnerability) in the three groups of indigents were based on chi-square testing (partial or complete tests) or mean comparison testing (ANOVA).

Bivariate means comparison tests identified no differences in the means of the key indicators between the excluded and retained observations, suggesting that cases were missing at random.

The test of difference in means was performed using a means comparison test (t test) of unequal variances (using both Satterthwaite's and Welch's formulas) in the Stata program.