Stats >> Statistical Training Opportunities At Children's Mercy Hospital (November 5, 2001)
This page is moving to a new website.
I have re-organized the data sets used in my training classes.
I've added some supplemental readings
and links to practice exercise sets.
The newest training classes
- Stats #73: Medical journals - The trouble with apples and oranges
- Stats #74: Use of diagnostic tests for making clinical decisions
- Stats #75: Open-access journals and their impact on research and the practice of medicine
- Stats #76: The post-modern assault on evidence-based medicine
- Stats #77: Bayesian tools for planning and monitoring accrual rates in clinical trials
I've also made some major updates to
Upcoming classes:
Topic: “What Do All These Numbers Mean? Confidence Intervals and P-Values”
Date: Friday, June 20, 2008
Time: 2:30 - 4:30 p.m.
Location: Hi-Ways
This class qualifies for 2 IRB Education Credits (IRBECs).
Topic: “Statistical Evidence: Apples or Oranges?”
Date: Thursday, August 28, 2008
Time: 1:00 p.m. - 4:00 p.m.
Location: HHC 535
This class qualifies for 3 IRB Education Credits (IRBECs).
Topic: “Using SPSS to Describe Your Data”
Date: Tuesday, September 9, 2008
Time: 1:00 – 4:00 p.m.
Location: OPC 1600
This class does not qualify for IRB Education Credits (IRBECs).
Topic: “What Do All These Numbers Mean? Odds Ratios and Relative Risks”
Date: Tuesday, September 16, 2007
Time: 1:00 - 3:00 p.m.
Location: Hi-Ways
This class does not qualify for IRB Education Credits (IRBECs).
Topic: “Statistical Evidence: Who Was Left Out?”
Date: Tuesday, September 23, 2008
Time: 11:45 a.m. - 12:45 p.m.
Location: By-Ways
This class qualifies for 1 IRB Education Credit (IRBEC).
Topic: “Using SPSS to Develop a Linear Regression Model”
Date: Tuesday, October 21, 2008
Time: 1:00 – 4:00 p.m.
Location: OPC 1600
This class does not qualify for IRB Education Credits (IRBECs).
Topic: “What Do All These Numbers Mean? Likelihood Ratios”
Date: Wednesday, October 29, 2007
Time: 1:00 - 3:00 p.m.
Location: HHC 535
This class does not qualify for IRB Education Credits (IRBECs).
Topic: “Statistical Evidence: Mountain or Molehill”
Date: Wednesday, November 12, 2008
Time: 11:45 a.m. - 12:45 p.m.
Location: Hi-Ways
This class qualifies for 1 IRB Education Credit (IRBEC).
Topic: “Using SPSS to Develop a Logistic Regression Model”
Date: Tuesday, November 25, 2008
Time: 1:00 – 4:00 p.m.
Location: OPC 1600
This class does not qualify for IRB Education Credits (IRBECs).
Topic: “What Do All These Numbers Mean? Regression Coefficients”
Date: Wednesday, December 10, 2008
Time: 11:45 a.m. - 12:45 p.m.
Location: Hi-Ways
This class does not qualify for IRB Education Credits (IRBECs).
Topic: “Statistical Evidence: Do the Pieces Fit Together?”
Date: Wednesday, December 17, 2008
Time: 1:00 p.m. - 4:00 p.m.
Location: HHC 535
This class qualifies for 3 IRB Education Credit (IRBECs).
Registration:
To register for any of Dr. Stephen Simon's classes, please go directly to the Master Event Calendar on The Scope. Find the date of the class you wish to attend, click on the class title, and then click to register. If you need further assistance, please contact Judy Champion in the Department of Medical Research, Biostatistics, ext.56784 or via Outlook email at jmchampion@cmh.edu.
NOTE: Signing up early for Dr. Simon's classes is encouraged and preferred. If there are insufficient attendees, the class will be cancelled/postponed within 24 hours prior to the scheduled start of the class.
Here's a quick list of all the classes. Click on a link to view the handout for that class.
SPSS Classes
- Stats #01: Using SPSS to Manage Your Research Data
- Stats #02: Using SPSS to Describe Your Data
- Stats #03: Using SPSS to Develop a Linear Regression Model
- Stats #04: Using SPSS to Develop a Logistic Regression Model
- Stats #05: Using SPSS to Develop a Survival Data Model
Simple Statistics
- Stats #10: Computing Simple Probabilities
- Stats #11: Computing Simple Descriptive Statistics
- Stats #12: Computing Simple Confidence Intervals
- Stats #13: Computing an Appropriate Sample Size
- Stats #17: Using Statistics to Monitor and Improve Quality
- Stats #18: Quality Control: A Hands-On Workshop
- Stats #18: Quality Control: A Hands-On Workshop (condensed version)
What Do All These Numbers Mean?
- Stats #21: What Do All These Numbers Mean? Sensitivity and Specificity
- Stats #22: What Do All These Numbers Mean? Confidence Intervals and P-Values
- Stats #23: What Do All These Numbers Mean? Odds Ratios and Relative Risks
- Stats #24: What Do All These Numbers Mean? Likelihood Ratios
- Stats #25: What Do All These Numbers Mean? Regression Coefficients
Statistical Evidence
- Stats #31: How to Read a Medical Journal Article (this class is obsolete)
- Stats #32: Statistical Evidence: Apples or Oranges? (Choice of the control group in research studies.)
- --> Stats #32a: Statistical Evidence. Apples or oranges? Randomized studies.
- --> Stats #32b: Statistical Evidence. Apples or oranges? Observational studies.
- --> Stats #32c: Statistical Evidence. Apples or oranges? Matching and adjustments.
- Stats #33: Statistical Evidence. Who Was Left Out? (Exclusions and dropouts in research studies.)
- Stats #34: Statistical Evidence. Mountain or Molehill? (Clinical Significance in research studies.)
- Stats #35: Statistical Evidence. Do the Pieces Fit Together? (Meta-analysis and Systematic Overviews).
- Stats #36: Statistical Evidence. Interviewing Other Witnesses. (Corroborating evidence for research findings)
Miscellaneous Classes
- Stats #41: Writing a Research Grant
- Stats #42: Designing a Research Study
- Stats #43: Guidelines for Good Graphics
- Stats #44: Things You Need to Know Before Starting a Research Project
- Stats #45: So You Want to Write a Questionnaire
Research Ethics
- Stats #51: The Ethics of Placebo Controlled Trials
- Stats #52: Scientific Validity, Statistics, and IRB Review
- Stats #53: Signal Detection Strategies for Paediatric Treatments
Seminar Series
- Stats #61: Controversies in Randomized Trials
- Stats #62: Statistical Evidence. Apples or Oranges?
- Stats #63: Statistical Evidence. Who Was Left Out?
- Stats #64: Statistical Evidence. Mountain or molehill?
- Stats #65: Is the Randomized Trial the Gold Standard for Research?
- Stats #66: What Can Alternative Medicine Teach Us About Evidence-Based Medicine?
- Stats #67: Meta-Analysis and Diagnostic Tests
- Stats #68: The use of control charts to track adverse events in clinical trials
- Stats #71: Control charts for continuous monitoring of the number needed to harm
- Stats #72: Manipulation of peer-review publications by pharmaceutical companies
- Stats #73: Medical journals - The trouble with apples and oranges
- Stats #74: Use of diagnostic tests for making clinical decisions
- Stats #75: Open-access journals and their impact on research and the practice of medicine
- Stats #76: The post-modern assault on evidence-based medicine
- Stats #77: Bayesian tools for planning and monitoring accrual rates in clinical trials
Which class should I take first?
It doesn't really matter much which class you take. All of the classes stand on their own and don't have any pre-requisites. The most popular class by far is Stats #01: "Using SPSS to Manage Your Research Data." Almost everyone has to worry about data management. It is the first step before any others. Another popular class, and one that is good to take early is Stats #02: "Using SPSS to Describe Your Data." It covers some very basic graphs and tables that are useful for almost every situation.
Can this class qualify for IRB Education Credits (IRBECs)?
After several discussions with Kathy Johnson, we tentatively agreed that classes talking about how to design a good research study should qualify for IRBECs. Many of my classes should therefore qualify. For now, I have identified classes 22, 32-35, 36, 42, 44, 51 and 52 as covering material relating to study design that would allow them to have IRBECs. The number of IRBECs would equal the length of the class, so a three hour class would earn you 3 IRBECs. This policy is still evolving. I will work closely with Kathy and with other members of the IRB to be sure that these classes address issues of importance from the IRB perspective.