Titlebook: SPSS for Starters and 2nd Levelers; Ton J. Cleophas,Aeilko H. Zwinderman Textbook 2016Latest edition Springer Nature Switzerland AG 2016 C

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One-Sample Continuous Data (One-Sample T-Test, One-Sample Wilcoxon Signed Rank Test, 10 Patients)esis is true. What hypothesis? Often, a nullhypothesis, which means no difference in your data from a zero effect. A zero effect indicates that a factor, like an intervention or medical treatment does not have any effect. The one sample t-test is adequate for assessment.

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Paired Continuous Data with Predictors (Generalized Linear Models, 50 Patients)treatments. However, they can not assess the effect of additional predictors like patient characteristics on the outcomes, because they have no separate predictor variables for that purpose. Generalized Linear Models can simultaneously assess the difference between two outcomes, and the overall effect of additional predictors on the outcome data.

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Unpaired Continuous Data (Unpaired T-Test, Mann-Whitney, 20 Patients), they involve independent treatment effects, i.e., with a zero correlation between the treatments. The two samples t-test, otherwise called the independent samples t-test or unpaired samples t-test, is appropriate for analysis.

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Linear Regression with Categorical Predictors (60 Patients)ke races, the race values 1–4 have no incremental function, and, therefore, linear regression is not appropriate for assessing their effect on any outcome. Instead, restructuring the data for categorical predictors does the job.

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Repeated Measures Analysis of Variance Plus Predictors (10 Patients)es. In this chapter repeated-measures ANOVA with predictor variables is reviewed. In addition to testing differences between the paired observations, it can simultaneously test the effects of the predictors on the outcome variables.

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Paired Continuous Data (Paired T-Test, Wilcoxon Signed Rank Test, 10 Patients)Studies where two outcomes in one patient are compared with one another are often called crossover studies, and the observations are called paired observations.

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Multiple Linear Regression (20 Patients)In the Chap. . linear regression was reviewed with one (binary) predictor and one continuous outcome variable. However, not only a binary predictor like treatment modality, but also patient characteristics like age, gender, and comorbidity may be significant predictors of the outcome.

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