Sumários
Mixed-effects models
11 Dezembro 2020, 14:00 • Rita Sousa
Mixed-effects models are becoming increasingly popular. One of the reasons is the need for studies with greater statistical power and more reliability on their reported findings. An approach to meet that need is to design research with more than one data point from each unit of analysis. However, when several observations come from the same unit of analysis (e.g., participant), they are usually correlated, and violate the independence assumption that is generally estimated on repeated-measures analyses. Consequently, it is essential to learn how to apply statistical models that accommodate for the non-independence, e.g., mixed-effects models, to accurately deal with interdependent data. The goal of this workshop is to introduce the linear mixed-effects models analysis, divided into 1) a theoretical part, focused on mixed-models key concepts; and 2) an applied, hands-on part, implementing the mixed-models analysis, interpreting the data and reporting the results.
A aula foi lecionada pela Professora Doutora Cláudia Simão.
Mixed-effects models
11 Dezembro 2020, 10:00 • Rita Sousa
Mixed-effects models are becoming increasingly popular. One of the reasons is the need for studies with greater statistical power and more reliability on their reported findings. An approach to meet that need is to design research with more than one data point from each unit of analysis. However, when several observations come from the same unit of analysis (e.g., participant), they are usually correlated, and violate the independence assumption that is generally estimated on repeated-measures analyses. Consequently, it is essential to learn how to apply statistical models that accommodate for the non-independence, e.g., mixed-effects models, to accurately deal with interdependent data. The goal of this workshop is to introduce the linear mixed-effects models analysis, divided into 1) a theoretical part, focused on mixed-models key concepts; and 2) an applied, hands-on part, implementing the mixed-models analysis, interpreting the data and reporting the results.
A aula foi lecionada pela Professora Doutora Cláudia Simão.
Mixed-effects models
10 Dezembro 2020, 14:00 • Rita Sousa
Mixed-effects models are becoming increasingly popular. One of the reasons is the need for studies with greater statistical power and more reliability on their reported findings. An approach to meet that need is to design research with more than one data point from each unit of analysis. However, when several observations come from the same unit of analysis (e.g., participant), they are usually correlated, and violate the independence assumption that is generally estimated on repeated-measures analyses. Consequently, it is essential to learn how to apply statistical models that accommodate for the non-independence, e.g., mixed-effects models, to accurately deal with interdependent data. The goal of this workshop is to introduce the linear mixed-effects models analysis, divided into 1) a theoretical part, focused on mixed-models key concepts; and 2) an applied, hands-on part, implementing the mixed-models analysis, interpreting the data and reporting the results.
A aula foi lecionada pela Professora Doutora Cláudia Simão.
Mixed-effects models
10 Dezembro 2020, 10:00 • Rita Sousa
Mixed-effects models are becoming increasingly popular. One of the reasons is the need for studies with greater statistical power and more reliability on their reported findings. An approach to meet that need is to design research with more than one data point from each unit of analysis. However, when several observations come from the same unit of analysis (e.g., participant), they are usually correlated, and violate the independence assumption that is generally estimated on repeated-measures analyses. Consequently, it is essential to learn how to apply statistical models that accommodate for the non-independence, e.g., mixed-effects models, to accurately deal with interdependent data. The goal of this workshop is to introduce the linear mixed-effects models analysis, divided into 1) a theoretical part, focused on mixed-models key concepts; and 2) an applied, hands-on part, implementing the mixed-models analysis, interpreting the data and reporting the results.
A aula foi lecionada pela Professora Doutora Cláudia Simão.
Systematic review of the literature and meta-analysis in Psychology
27 Novembro 2020, 14:00 • Rita Sousa
Systematic review of the literature and meta-analysis in Psychology
In this seminar, we will discuss a) the typology of literature reviews and syntheses (e.g., systematic/non-systematic, narrative/quantitative) and the advantages of systematic reviews and meta-analyses; and b) the strength of empirical evidence as function of the quality of studies and respective methodological design. We will then focus on the statistical procedures for the estimation, meta-analytic combination, and analysis of the heterogeneity of effect sizes. These features will be complemented with practical exercises.
Esta aula foi lecionada pelo Prof. Fernando Ferreira-Santos.