Services

CAPES has the capacity to help in planning grants that include educational and social science research and/or evaluation. We have wide ranging experience in developing plans for educational interventions and building evaluation of grants with human subjects. Our expertise includes planning research and evaluation with quantitative and qualitative research methods. We can help in the design of studies that require a range of types of data collection including experimental studies, quasi-experimental studies, correlational studies and surveys.

CAPES has the capacity to conduct program evaluations on educational and social science aspects of grants. CAPES provides support in data gathering, data management and quality assurance. We provide support in the ethical collection of data including assistance in IRB applications and guaranteeing the confidentiality or anonymity of the data collection. We have expertise in data collection and data management for quantitative and qualitative data. CAPES will provide instrument construction, instrument validation and reliability analyses.

CAPES provides consultation for research and evaluation. We provide expertise in data analysis for quantitative and qualitative data analysis and interpretation. For quantitative analyses, CAPES has experience with a wide range of statistical modeling techniques including regression analysis, longitudinal data analysis, hierarchical linear modeling, structural equation modeling (SEM), and other multivariate statistical procedures. CAPES also provides a wide range of psychometric services including item response theory and generalizability theory.

1. Planning evaluations of projects that include quantitative, qualitative, and mixed methods
2. Formulating testable research hypotheses
3. Determining sample sizes required for research studies
4. Identifying potential confounding variables
5. Recommending appropriate data analysis plans
6. Recommending data collection forms to improve the quality and completeness of data collection and ease of entry into a computerized dataset
7. Structuring research data into a database to ease future analysis, create tables and graphs, and support unanticipated queries
8. Formulating budgets for proposals to support evaluation, statistics, and computing-related costs
9. Writing applications to the Institutional Review Board
10. Designing data collection instrumentation
11. Designing research databases and implementation plans
12. Assuring data quality control and data confidentiality
13. Documenting databases
14. Creating public use datasets
15. Overseeing the design, implementation, and analysis of sample surveys
16. Analyzing quantitative data including ANOVA, regression, hierarchical linear modeling, logistic regression, and structural equation modeling
17. Analyzing qualitative data including thematic, grounded theory, phenomenological, narrative, discourse, document, political, and visual analysis
18. Analyzing the reliability and validity of measurement data using factor analysis, classical test theory, generalizability theory, and item response theory