Class Métodos de Investigação em Ciberterapia e Reabilitação Neurocognitiva II

  • Presentation


    Deepening of the topics discussed in the UC of Research Methods in Cybertherapy and Neurocognitive Rehabilitation I.

  • Code


  • Syllabus


    1. Methods and data analysis in Cybertherapy and Neurocognitive Rehabilitation 1.1 Descriptions, correlations, and reliability of measures 2. Validity 2.1. Types of validity and statistical procedures 2.2. Exploratory analysis using principal components analysis

    2.3. Item response theory (Rasch) 3. Sensitivity and specificity 4. Types and study designs 4.1. Cross-sectional studies 4.2. Prospective and retrospective longitudinal studies 5. Intra- and inter-subject conditions 5.1. Clinical Significance and Reliable Change Index 6. Hypothesis Testing 6.1. Analysis of Variance 6.2. Linear Regression 6.3. Interpretation and writing of results 6.4. Generalization and replicability 7. Scientific dissemination 

  • Objectives


    This curricular unit aims to provide skills in the scientific method, measurement models and data analysis in Cybertherapy and Neurocognitive Rehabilitation. Specifically, it is intended that students develop skills related to the psychometric study of psychological and neuropsychological instruments and data analysis for the given study type and design in Cybertherapy and Neurocognitive Rehabilitation, as well as the level of dissemination of results via scientific paper.

  • Teaching methodologies and assessment

    Teaching methodologies and assessment

    Expositive and demonstrative methodologies. With this CU it is intended that students acquire knowledge about the scientific method integrated in the main statistical procedures used in this area. The expository method will be used to explain the theoretical foundations, threats to the validity of a research, main types and designs of studies in this area. The demonstrative method will assume greater importance and will be based on the main methodologies of data analysis. The evaluation is based on the work done in class and should result in the writing of a report of the data analysis carried out in class. The final exam focuses on the contents of the theoretical and practical classes (100%). Class attendance is mandatory. It is expected that the performance in the different moments of evaluation will guarantee the acquisition of the necessary skills for the approval in this curricular unit. 

  • References


    APA (2010). Publication manual of the American Psychological Association (6th ed.). Washington: APA. Field, A. (2017). Discovering Statistics using IBM SPSS Statistics (5th Ed.) London: Sage Publications Ltd. Kline, T. (2005). Psychological testing. A practical approach to design and evaluation. London: Sage Publications. Linacre, JM. (2002). Optimizing rating scale category effectiveness. Journal of Applied Measurement, 3, 85-106. Linacre, JM. (2013). A user´s guide to Winsteps Ministep– Rasch-model computer programs. Chicago: Winsteps Stevens, J.P. (2016). Applied multivariate statistics for the social sciences (6th Ed.). London: Lawrence Erlbaum Associates, Inc. Tabachnick, B. G. & Fidel, L. S. (2013). Using Multivariate Statistics (6th Ed.). Boston: Pearson. Wilson, M. (2004). Constructing measures: A item response modelling approach. London: Lawrence Erlbaum Associates, Inc.

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