| Topic |
Sub-topic |
| LESSON 1. RESEARCH PLAN |
Structure of a research. Activities in a research: measurement, comparison and interpretation. |
| LESSON 2. TIPES OF EPIDEMIOLOGICAL STUDIES. |
Descriptive studies vs. analytical studies. Cross-sectional studies vs. longitudinal studies. Experimental studies vs. observational studies. Prospective studies vs. retrospective studies. Questions of validity, accuracy and reliability in epidemiological studies. |
| LESSON 3. FUNDAMENTALS ON CLINICAL EPIDEMIOLOGY. |
The clinical decision. Statistical significance vs. clinical relevance. Causal inference. |
| LESSON 4. MEASURES OF DISEASE FREQUENCY. |
Incidence. Prevalence. Adjusting rates. Effect measures. Risk. Risk measurement. Early detection of diseases. |
| LESSON 5. FUNDAMENTALS ON STATISTICS. |
The concept of Statistics. Variables. Tabulation and graphical representation of variables. |
| LESSON 6. DESCRIPTIVE STATISTICS. |
Descriptive statistical analysis. Measures of central tendency. Measures of dispersion. Measures of frequency distribution. The normal curve. Features and applications of the normal curve. Calculation of probabilities. |
| LESSON 7. SAMPLING. |
The concept of sampling. Applications. Sampling types. Calculation of the sample size and sampling errors. |
| LESSON 8. INFERENCIAL STATISTICS. |
Introduction to inferential statistics. Parameter estimation and hypothesis testing. Mean difference. Difference in proportions. Confidence intervals. |
| LESSON 9. BASIC OPERATIONS IN SPSS. |
SPSS windows. Creating variables in SPSS. Previous operations on the data. Variable transformation. |
| LESSON 10. BIVARIATE ANALYSIS. |
Analysis of variance. Analysis of contingency tables. Correlation analysis. SPSS applications. |
| LESSON 11. ANALYSIS OF SURVIVAL AND MATCHING. |
Analysis of survival. ROC curves. Study of the agreement. SPSS applications. Presentation and interpretation of results. |
| LESSON 12. EXPLORATORY DATA ANALYSIS. |
Graphic / exploratory analysis of the variables. SPSS applications. |
| LESSON 13. MULTIPLE REGRESSION ANALYSIS. |
Concept of multiple regression analysis. Objectives of multiple regression. Design research in multiple regression analysis. Assumptions in the multiple regression analysis. Estimation and assessment of the regression model. Interpretation of the theoretical value of the regression. Validation of results. Examples of application of multiple regression analysis in SPSS. |
| LESSON 14. LOGISTIC REGRESSION ANALYSIS. |
Concept of logistic regression analysis. Binomial and multinomial logistic regression. Objectives of the logistic regression. Design research in logistic regression analysis. Assumptions in the logistic regression analysis. Estimation and evaluation of the logistic regression model. Interpretation of the theoretical value of the regression. Validation of results. Application examples in binomial and multinomial logistic regression analysis in SPSS. |
| LESSON 15. MULTIVARIANTE ANALYSIS OF VARIANCE. |
Concept of multivariate analysis of variance (MANOVA). MANOVA applications. MANOVA objectives. Research design by MANOVA. Basic assumptions of MANOVA. MANOVA model estimation and assessment of global adjustment. Interpretation of the results of MANOVA. Validation of results. Examples of application of MANOVA in SPSS. |
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