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Update for Spring 2025
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31 changes: 16 additions & 15 deletions docs/content.md
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| **Week** | Topic |
| :-: | :-- |
|[**Week 1**](week1.md) <br /> M 8/26 | Communication |
|**No Class** <br /> M 9/2 | Labor Day |
|[**Week 2**](week2.md) <br /> M 9/9 | The Practice of Statistical Consulting |
|[**Week 3**](week3.md) <br /> M 9/16 | Exploratory Analysis |
|[**Week 4**](week4.md) <br /> M 9/23 | Practice Consultations |
|[**Week 5**](week5.md) <br /> M 9/30 | Investigator Meeting |
|[**Week 6**](week6.md) <br /> M 10/7 | Statistical Mistakes |
|[**Week 7**](week7.md) <br /> M 10/14 | Communicating Statistical Concepts |
|[**Week 8**](week8.md) <br /> M 10/21 | Check-In I |
|[**Week 9**](week9.md) <br /> M 10/28 | Practice Consultations II |
|[**Week 10**](week10.md) <br /> M 11/4 | Presenting Statistical Information |
|[**Week 11**](week11.md) <br /> M 11/11 | The Statistician's Role |
|[**Week 12**](week12.md) <br /> M 11/18 | Check-In II |
|[**Week 13**](week13.md) <br /> M 11/25 | Ethics |
|[**Week 14**](week14.md) <br /> M 12/2 | Investigator Meeting: Final Presentation |
|[**Week 1**](week1.md) <br /> M 1/13 | Communication |
|**No Class** <br /> M 1/20 | MLK Holiday |
|[**Week 2**](week2.md) <br /> M 1/27 | The Practice of Statistical Consulting |
|[**Week 3**](week3.md) <br /> M 2/3 | Exploratory Analysis |
|[**Week 4**](week4.md) <br /> M 2/10 | Practice Consultations |
|**No Class** <br /> M 2/17 | President's Day |
|[**Week 5**](week5.md) <br /> M 2/24 | Investigator Meeting |
|[**Week 6**](week6.md) <br /> M 3/3 | Statistical Mistakes |
|[**Week 7**](week7.md) <br /> M 3/10 | Communicating Statistical Concepts |
|**No Class** <br /> M 3/17 | Spring Break |
|[**Week 8**](week8.md) <br /> M 3/24 | Check-In I |
|[**Week 9**](week9.md) <br /> M 3/31 | Practice Consultations II |
|[**Week 10**](week10.md) <br /> M 4/7 | Presenting Statistical Information |
|[**Week 11**](week11.md) <br /> M 4/14 | The Statistician's Role / Check-In II |
|[**Week 12**](week12.md) <br /> M 4/21| Ethics |
|[**Week 13**](week13.md) <br /> M 4/28 | Investigator Meeting: Final Presentation |
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# PM516a: Introduction to Biostatistical Consulting (aka Statistical Problem Solving)

## Welcome!
Welcome to PM516a: Introduction to Biostatistical Consulting for Fall 2024! This semester we will learn skills to become an effective consultant and work with an investigator at Keck on an actual research problem.
Welcome to PM516a: Introduction to Biostatistical Consulting for Spring 2025! This semester we will learn skills to become an effective consultant and work with an investigator at Keck on an actual research problem.

This course should be useful for:

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PM516A: Statistical Problem Solving
1 Unit
Monday 5:10-6:00pm
SSB115
Monday 5:00-5:50pm
SSB110

## Course Overview
### Course Description
Expand Down Expand Up @@ -44,26 +44,48 @@ There are three broad categories of activites for this course:
* Skills development for presenting statistical results, which will improve the effectiveness of the statistician being able to communicate results to their client.
* Participation in a real consultation as a group with an investigator client at USC.

This course is graded credit/no credit and there is no point breakdown. Instead, student must complete <u>all</u> of the following:
This course is graded credit/no credit and there is no point breakdown. Instead, students must complete <u>all</u> of the following:

#### Required Trainings
Students will be working with real data from investigators at USC and must complete the appropriate required trainings. There are two trainings offered by CITI (https://about.citiprogram.org/) that must be completed by the third week of class:
Students will be working with real data from investigators at USC and must complete the appropriate required trainings. There are two trainings offered by CITI (https://about.citiprogram.org/) that must be completed by the third class session:

* CITI Biomedical Human Subjects
* CITI Responsible Conduct of Research
* CITI Research HIPAA
* Students may need to complete additional project-specific trainings

#### Weekly Activities
Students will participate in weekly activities to improve their consulting and statistical analysis skills. In order to get the most of these activities, students must complete required pre-class preparation, which may include reading articles, excerpts from the textbook, or watching videos. Students will use the information from these pre-class preparation activities in the live session, and will receive credit if they actively participate in at least 10 sessions. Partial credit will be given if the student attends but does not actively participate in a live class session.
Students will participate in weekly activities to improve their consulting and statistical analysis skills. In order to get the most of these activities, students must complete required pre-class preparation, which may include reading articles, excerpts from the textbook, or watching videos. Students will use the information from these pre-class preparation activities in the live session.

#### Investigator Meeting
Students will be meeting with a collaborator at USC (e.g., from Keck School of Medicine, Children’s Hospital Los Angeles, etc.) and will work on a project as a group. Any meeting with the investigator is mandatory. Because this course teaches skills applicable in a consulting setting, students must be on time for the meeting and must be an <u>alert, active participant</u> with their <u>camera on</u>.

#### Final Presentation
The final day of class will be a presentation to the client collaborator. Students will present in groups, and each student must contribute to the presentation. At the end of the meeting, there will be a brief period for the students and client to provide feedback on the experience.

### Late Submission Policy
Assignments cannot be completed outside of the in-class context. However, there may be opportunities for alternate make-up assignments in rare circumstances.
## Grading Breakdown

| **Assignment** | Criteria |
| :-: | :-- |
|Weekly Activities | Actively participate in at least 10 sessions. Half-credit will be given if the student attends but does not actively participate. Students can make up for a missed class session via a written assignment. |
|Required Trainings | Complete the required CITI trainings by the third class session. |
|Investigator Meeting | Actively participate in the preliminary investigator meeting. |
|Final Presentation | Substantially contribute to the final project, including presenting part of the final group presentation. |

## Classroom Norms
1. **Take Charge of Your Learning** - As a graduate-level course, this is an opportunity to deepen your expertise and develop new skills in your academic field. Your success depends on active engagement and responsibility in the learning process. Feel empowered to ask questions, seek clarification, and communicate barriers early with the instructor. Make use of all resources available to you, including office hours, peer support, and additional readings.
2. **Be Present** – This is a practice-based course, and active participation is key to your success as a consultant. “Being present” means not just physically attending class sessions, but fully engaging in every class session through focus, contribution to discussions, and participation in activities. Your active involvement during class time will deepen your understanding of the field and help you develop useful skills.
3. **Practice Professionalism** – In this course, you will engage with your fellow students, but also external collaborators who are professionals in the field. It is essential to conduct yourself with professionalism in all interactions with them and with your fellow classmates. This includes being punctual, communicating clearly and respectfully, and representing you and your program with integrity. Come to sessions prepared, showing respect for the time and expertise of others. The way you conduct yourself in these interactions will contribute to your growth and future success in the field.

## Policy on the Use of AI Generators
The use of AI (e.g., ChatGPT) can sometimes be helpful when conducting statistical analysis and interpreting results. However, in my experience the use of AI has led to incorrect, misleading, or otherwise false results in a surprising number of cases. As such, I discourage the use of AI as the “final arbiter” of conducting and interpreting data analyses. Keep in mind the following:
• You may use AI tools to help aggregate and/or explain ideas related to this course, and some assignments will ask you to use these tools to generate hypothetical scenarios for you to examine.
• Only use these tools if you have sufficient training and experience in the methods you are asking AI tools to help you with. The output of such tools must be examined through a critical lens, and using such tools blindly can be dangerous.
• Be mindful of when AI is most useful. Consider its appropriateness in each situation.
• Do not assume the information provided by AI tools is accurate or trustworthy. In fact, assume all information is incorrect unless you can verify its accuracy with another source. You will be responsible for any errors or omissions provided by the tool.
• If you use AI tools for any deliverable, you are expected to clearly attribute any material generated by the tool used.



## Course Schedule
[Weekly Content](content.md)
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## Course Overview
### Course Description
This course serves to expose students to the practice of biostatistical consulting. It will help statisticians and data analysts develop the skills necessary for interacting with non-biostatistician collaborators. Under faculty supervision, the student will meet with an investigator, independently conduct statistical analysis, and communicate their findings.
This course will reinforce concepts in biostatistical consulting and will expose students to the applied practice of biostatistical consulting. It will help statisticians and data analysts practice the necessary skills for successfully interacting with non-statistician collaborators. Under faculty supervision, the student will meet with an investigator and independently conduct statistical analysis throughout the semester.

### Learning Objectives
Through this course, students will gain additional experience with statsitical consulting. Students will:
* Demonstrate the consulting principles learned in PM516a
* Improve their skills when determining a statistical problem and analysis plan
* Use statistical tools to produce a meaningful analysis
* Effectively communicate the results of their analysis in a statistical report
* Improve the quality of their statistical interactions with non-statistician collaborators
* Understand how to work with individuals from diverse content domains
Through this course, students will gain additional experience in statistical consulting. Students will:
• Recall and apply the consulting principles learned in PM516a.
• Summarize research questions and implement appropriate biostatistical methods to address such questions, understanding how different methodologies affect conclusions.
• Apply statistical tools they have learned in their program to produce a meaningful analysis.
• Evaluate statistical interactions with non-statistician collaborators to improve the quality of such interactions.
• Understand how to work with individuals from diverse content domains.
• Create comprehensive, coherent consulting reports and interpret analyses for dissemination materials, such as the results sections of a manuscript.


### Course Preparation
Prerequisites: PM516a (this course assumes familiarity with basic statistics and regression analysis)

## Course Requirements
## Assessments

### Communication
Blackboard (data sets, assignment submission), website (course materials), USC e-mail and Slack (communication)
Students will each be assigned a project and will use the semester to perform statistical analyses and create an analysis report for the client collaborator. As a 1-unit course, students are expected to spend approximately 30 hours on the analysis and writing of the project. All work should be completed before the last day of class.

### Textbook
Cabrera J, McDougall A. Statistical Consulting. SPringer Science & Business Media; 2002 Jan 2.
This course is graded credit/no credit and there is no point breakdown. Instead, students must complete <u>all</u> of the following:

### Required Software
Students must have proficiency in at least one statistical program, but may choose which to use for this course (e.g., R, SAS, Stata, SPSS).
### Required Trainings
Students will be working with real data from investigators at USC and must complete the appropriate required trainings. There are three trainings offered by CITI (https://about.citiprogram.org/) that must be completed by the third week of the semester:

## Assessments
* CITI Biomedical Human Subjects
* CITI Responsible Conduct of Research
* CITI Research HIPAA
* Students may need to complete additional project-specific trainings

### Grading Breakdown
### Required Meetings <u>with Deliverables</u>
This is a practicum-type course and students will develop additional skills through their interactions with the instructor and collaborator. Students must proactively schedule at least 5 meetings over the semester:
* Initial Meeting. Once the project is assigned, the student will schedule a meeting with the collaborator (and instructor, if possible). After the meeting, the student must send the collaborator and instructor a consultation follow-up e-mail that discusses the scope of work and appropriate timelines for the project.
* Interim Meetings. At least one interim meeting should be scheduled with the instructor and client collaborator to discuss statistical or substantive issues with the analysis, with additional meetings on an as-needed basis.
* Final Meeting (Instructor). Before presenting the final analyses to the collaborator, the student should schedule a meeting with the instructor to review the accuracy and interpretation of results to be presented.
* Final Meeting (Collaborator). The final meeting will be focused on presenting the analyses to the collaborator (and instructor should be included, if possible).

| Category | Points |
| :--- | :--: |
| Scope of Work | 10 |
| Meetings | 30 |
| Progress Report | 20 |
| Final Project | 40 |
| Total | 100 |
### Analysis Report
An analysis report should be delivered to the collaborator in advance of the final meeting. There are different ways to accomplish this. For example, the PM516a textbook offers one template, while I use the template at (https://uscbiostats.github.io/PM516/analysis-report/). Be sure to use all principles learned in PM516a when completing the analysis report.

Students will receive credit for the course if they achieve >80 points.
### Debriefing

### Late Submission Policy
Students are expected to work independently and adhere to all deadlines. Reports will be expected by collaborators on the dates promised, and late reports will result in a penalty for every day submitted past the due date. Late final projects are not accepted except under verifiable extenuating circumstances.
By the end of the semester, students must submit documentation of the hours worked, much like a consultant would submit an invoice of their work performed. The template will be provided to the students.

### Description of Assessments
**The Scope of Work** will contian information about the statistical project the student is working on, the amount of work and types of analyses to be performed, and a timeline and deliverables for the project.
**Meetings** will occur between the student and the instructor/collaborator(s) no fewer than three times during the semester. In these meetings the student may discuss issues relating to planning, implementing, and/or interpreting the statistical analyses.
**Progress Report** will ensure progress and will be due midway throught he course. It will consist of an outline of the analysis report that will be presented.
**The Final Project** is an analysis report that will address the researcher's question from the consultation..
After presenting the final analysis report, the collaborator will be sent an evaluation form for constructive feedback on the student’s performance. Students should acknowledge the receipt of this feedback. This evaluation serves as feedback to the student but will not affect their final grade in the course.

## Course Schedule
| **A** | Topic |
| :-: | :-- |
|**Week 1** <br /> M 5/22 | Communication |
|**Week 2*** <br /> M 5/29 | Exploratory Analysis |
|**Week 3** <br /> M 6/5 | Practice Consultations |
|**Week 4** <br /> M 6/12 | Investigator Meeting |
|**Week 5*** <br /> M 6/19 | Project Review |
|**Week 6*** <br /> M 6/26 | Tables & Figures |
|**Week 7*** <br /> M 7/3 | Critical Consult Review |
|**Week 8** <br /> M 7/10 | Project Check-In |
|**Week 9** <br /> M 7/17 | Communicating Results |
|**Week 10** <br /> M 7/24 | Final Presentation |

| **B** | Topic |


## Grading Breakdown

| **Assignment** | Criteria |
| :-: | :-- |
|**Week 1** <br /> M 5/22 | The Practice of Statistical Consulting |
|**Week 2*** <br /> M 5/29 | Reproducibility |
|**Week 3** <br /> M 6/5 | Practice Consultations |
|**Week 4** <br /> M 6/12 | Investigator Meeting |
|**Week 5*** <br /> M 6/19 | Project Review |
|**Week 6*** <br /> M 6/26 | Personality Types |
|**Week 7*** <br /> M 7/3 | Critical Consult Review |
|**Week 8** <br /> M 7/10 | Project Check-In |
|**Week 9** <br /> M 7/17 | Ethics |
|**Week 10** <br /> M 7/24 | Final Presentation |

*There will be no live session on weeks marked with a* *
|Required Trainings | Complete the required trainings before the third week in the course. |
|Instructor Meetings | Schedule at least 2 meetings with the instructor, one of which will focus on reviewing your completed analysis report. |
|Investigator Meetings | Schedule at least 3 meetings with the investigator: an initial meeting, a check-in meeting, and a final presentation meeting. |
|Analysis Report | Successfully complete and submit your analysis report. |
|Debriefing | Successfully complete your mock invoice and receive collaborator feedback. |

## Classroom Norms
1. **Take Charge of Your Learning** - As a graduate-level course, this is an opportunity to deepen your expertise and develop new skills in your academic field. Your success depends on active engagement and responsibility in the learning process. Feel empowered to ask questions, seek clarification, and communicate barriers early with the instructor. Make use of all resources available to you, including office hours, peer support, and additional readings.
2. **Be Present** – This is a practice-based course, and active participation is key to your success as a consultant. “Being present” means not just physically attending class sessions, but fully engaging in every class session through focus, contribution to discussions, and participation in activities. Your active involvement will deepen your understanding of the field and help you develop useful skills.
3. **Practice Professionalism** – In this course, you will engage with your fellow students, but also external collaborators who are professionals in the field. It is essential to conduct yourself with professionalism in all interactions with them and with your fellow classmates. This includes being punctual, communicating clearly and respectfully, and representing you and your program with integrity. Come to sessions prepared, showing respect for the time and expertise of others. The way you conduct yourself in these interactions will contribute to your growth and future success in the field.


## Statement on Academic Conduct and Support Systems
### Academic Conduct
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