HMGT 400 Group Project

Assignment #3 – Group Project

This is not more than a 20-page submission. In this assignment, students will go through the steps to set up a quantitative research study. The Instructor will divide the class into groups to complete the assignment in week 1. Each group should submit 1 topic selection in week 1, and 1 final report. This report should include qualitative and quantitative sections. Here are the main steps to perform this team project:

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Step #1: Topic selection

The instructor will provide a list of topics; the team also should submit the team agreement plan with the selected topic in week 1 for the faculty feedback and approval.

Step #2: Performing Qualitative analysis

2.1. This section of the assignment is aimed at giving students an opportunity to select and analyze at least 5 articles using the ‘Review Manager 5’ tools to analyze the risk of bias for 5 selected articles following these steps:

– The methodological quality and risk of bias evaluation of the selected studies should be conducted independently by two team members, following the Cochrane Handbook for Systematic Reviews (Higgins, 2011), a domain-based evaluation for each study should be done across five domains:

– Selection bias,

– Performance bias,

– Detection bias,

– Attrition bias, and

– Reporting bias.

The judgment of studies for potential bias should be indicated by assigning ‘low risk’, ‘high risk, or ‘unclear risk’, for each respective source of bias.

Reference

Cochrane Handbook for Systematic Reviews of Interventions. (n.d.). Retrieved July 12, 2019, from https://training.cochrane.org/handbook

2.2. Report your finding using the Bias-Tables and Bias-Plots.

Table 1: Literature Review Analysis

Authors, Year of Publication

Intervention/

Policy evaluated

Study design/

Time Period

Data/

Study Population

Relevant Findings/

Recommendations

Author1, YYYY

 

 

 

 

Author2, YYYY

 

 

 

 

Author3, YYYY

 

 

 

 

Author4, YYYY

 

 

 

 

Author5, YYYY

 

 

 

 

 

Table 2. Literature Review, Table of Biases

 

Selection Bias

Performance Bias

Detection Bias

Attrition Bias

Reporting Bias

Authors

Systematic differences between baseline characteristics of the groups that are compared.

Systematic differences between groups in the care that is provided, or in exposure to factors other than the interventions of interest.

Systematic differences between groups in how outcomes are determined.

Systematic differences between groups in withdrawals from a study.

Systematic differences between reported and unreported findings.

Author1, 2019

Y

Y

Y

Y

Y

Author2, 2019

 

 

 

 

 

Author3, 2019

 

 

 

 

 

Author4, 2019

 

 

 

 

 

Author5, 2019

 

 

 

 

 

Note: Y: Low risk, N: High risk, U: Unclear

 

Step #3: Performing Quantitative data analysis design. This is very similar to Individual Assignments 1 and 2 (please look at the instructions for more details).

For this section:

3.1. Select one of the class data sets

3.2. Identify relevant variables

3.3. Indicate the statistical method you used for your analysis

3.4. Identify the statistical software your team used to run the statistical analysis focusing on EXCEL or RStudio (BONUS points) as the main software (you can use any other software such as SAS, STATA or SPSS, but the master-code will be available only for RStudio)

3.5. Analyze the data, state your conclusions and support them, this section should include:

3.5.1. Hypothesis or research questions with a short paragraph to discuss the issue.

3.5.2. Research Method for this section first report the table of variables, then define the variables using the example provided in step-by-step instruction.

3.5.3. Report the software and type of analysis you performed in this section including descriptive table and plots

3.5.4. Discuss your findings

3.5.5. Discussion: for this section, compare your finding with the LR (literature review) you performed in the first section

3.5.6. Recommendations: suggest a few policy recommendations based on your findings and LR.

Note: Make sure to submit your RStudio codes for your instructor review (for BONUS points).

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