18.2.3 Example of an analysis of case series data.18.2.2 A study using multiple baseline across behaviours: Effectiveness of electropalatography.18.2.1 A multiple baseline design: Speech and language therapy for adolescents in youth justice.18.2 Examples of studies using different types of single case design.17.1.1 Delayed crossover design (Wait list controls).17.1 A within-subjects approach to the RCT.14 Moderators and mediators of intervention effects. 13.3 Heterogeneity and personalized intervention.13.2 Transfer to real life: efficacy and effectiveness.13.1 Inefficiency: need for unfeasibly large samples.12.2.5 Linear mixed models (LMM) approach.12.2.4 Analysis of covariance on outcome scores.12.2.1 Sample dataset with illustrative analysis.12.2 Steps to take before data analysis.12 The randomized controlled trial as a method for controlling biases.11.3.4 Improving power by use of multiple outcomes.11.3.3 Extracting a principal component from a set of measures.11.3 Adjusting statistics for multiple testing.11 False positives, p-hacking and multiple comparisons.10.3 Sample size affects accuracy of estimates.10 How big a sample do I need? Sampling, statistical power and type II errors.9.2 Dropouts after recruitment: Intention to treat analysis.9 Further potential for bias: volunteers, dropouts, and missing data.8.2 The importance of masking for assessments.7.2 Units of analysis: Individuals vs clusters.7 Controlling for selection bias: randomized assignment to intervention.6.2 Possible adverse effects of intervention.6.1 Is it ethical to include a control group?.6 Controlling unwanted effects with a control group.5 Limitations of the pre-post design: biases related to systematic change.4.2 Identifying specific intervention effects by measures of mechanism.4 Improvement due to nonspecific effects of intervention.3.2.5 Subjectivity as a threat to validity.3.2.4 Functional outcomes vs test scores.3.2.3 Generalisability of results to other outcomes: the concepts of far and near transfer.2 Why clinical observations can be misleading.1.1 How can we know if we’ve made a difference?.
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