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1 The Wilcoxon rank-sum test was used to assess differences between groups.
2 Analysis of variance was used to assess differences of cognitive and motor development.
3 Logistic regression was used to assess differences in UAD indices between phenotype groups.
4 Aim: To assess differences in treatment of ischaemic heart disease in the Scandinavian countries.
5 Zero-inflated Poisson models were used to assess differences in absenteeism between cyclists and non-cyclists.
6 Bivariate analysis and ordinal logistic regression were done to assess differences between the groups.
7 Survival curve and Cox proportional hazards analyses were conducted to assess differences between groups.
8 Statistical analysis was used to assess differences in image quality according to scanning parameter levels.
9 Generalized estimating equations were used to assess differences in longitudinal outcomes between cases and controls.
10 Survival analysis was used to assess differences between regimens.
11 A mixed factorial ANOVA was carried out to assess differences in the effectiveness between treatments.
12 Analysis of covariance was used to assess differences over time between the control and intervention regions.
13 We applied multilevel linear and logistic regression models to assess differences between countries and LTCF types.
14 These patients were stratified according to the main prognostic variables, to assess differences with N(+) cases.
15 Nonparametric tests were used to assess differences , and receiver operating characteristic analysis was performed for optimal threshold calculations.
16 Independent t-tests and χ(2) tests were used to assess differences in continuous and categorical variables, respectively.
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This collocation consists of: Assess differences through the time
Assess differences across language varieties