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I've been asked to develop a series of training classes, which I may also use as a series of monthly webinars (web seminars). Here's a first draft. All classes are two hours long. Classes are self-contained and do not need to be taken in the order listed below. There are no prerequisites other than the ability to use a pocket calculator.

October 2009 :

What do all these numbers mean? P-values and confidence intervals and the Bayesian alternative.Based on Chapter 6 ofStatistical Evidenceand on www.cmh.edu/stats/training/hand22.asp and new material. In this class you will learn how to:

- distinguish between statistical significance and clinical significance;
- define and interpret p-values;
- explain the ethical issues associated with inadequate sample sizes.
- explain the difference between informative and diffuse priors;
- interpret statistics from a posterior distribution.
November 2009:

What do all these numbers mean? Sensitivity, specificity, and the likelihood ratio.Based largely on Chapter 6 ofStatistical Evidenceand on www.cmh.edu/stats/training/hand21.asp and www.cmh.edu/stats/training/hand24.asp. In this class, you will learn how to:

- compute sensitivity and specificity;
- identify the problems with diagnosing a rare disease;
- understand which tests are useful for ruling in or ruling out a disease.
Based largely on Chapter 6 of

Statistical Evidenceand on www.cmh.edu/stats/training/hand21.asp and www.cmh.edu/stats/training/hand24.asp.December 2009:

What do all these numbers mean? Odds ratios, relative risks, and number needed to treat.Based largely on Chapter 6 ofStatistical Evidenceand on www.cmh.edu/stats/training/hand23.asp. In this class you will learn how to:

- list the advantages of the odds ratio;
- list the advantages of the relative risk;
- compute and interpret the number needed to treat.
January 2010:

What do all these numbers mean? Linear and logistic regression coefficients.Based largely on Chapter 6 ofStatistical Evidenceand on www.cmh.edu/stats/training/hand25.asp. In this class you will learn how to:

- Interpret the slope coefficient in a linear regression model;
- Identify problems with extrapolation in linear regression;
- Explain why the logistic regression model uses log odds units.
February 2010:

Evidence Based Medicine: Randomization.Based largely on Chapter 1 ofStatistical Evidenceand on www.cmh.edu/stats/training/hand32a.asp. In this class you will learn how to:

- create a randomized list of treatments;
- understand the practical and ethical limitations to randomized studies;
- describes three variations on randomization.
March 2010:

Evidence Based Medicine: Observational studies.Based largely on Chapter 1 ofStatistical Evidenceand on www.cmh.edu/stats/training/hand32b.asp. In this class you will learn how to:

- contrast the selection process in a cohort design with a case-control design;
- describe the limitations of a case-control design for evaluating a diagnostic test;
- appraise the extent of temporal bias in the historical-controls design.
April 2010:

Evidence Based Medicine: Statistical adjustments to control for bias.Based largely on Chapter 1 ofStatistical Evidenceand on www.cmh.edu/stats/training/hand32c.asp. In this class you will learn how to:

- apply matching and stratification to prevent covariate imbalance;
- discuss the strengths and weaknesses of crossover studies;
- explain how covariate adjustment and weighting work to reduce or remove bias.
May 2010:

Evidence Based Medicine: Exclusions and dropouts in clinical trials.Based largely on Chapter 2 ofStatistical Evidenceand on www.cmh.edu/stats/training/hand33.asp. In this class you will learn how to:

- assess the impact of dropouts in a research study;
- describe how intention to treat is used in studies with compliance issues;
- explain how the ethical need for informed consent research can limit generalizability.
June 2010:

Evidence Based Medicine: Clinical significance.Based largely on Chapter 3 ofStatistical Evidenceand on www.cmh.edu/stats/training/hand34.asp. In this class you will learn how to:

- explain how a narrow focus provides better quality evidence;
- assess the impact of post hoc protocol changes;
- evaluate the quality of outcome measures;
- recognize the ethical and practical limitations of a study when the sample size is too small;
September 2010:

Evidence Based Medicine: Bias and fraud in research studies.Based on new material and on Chapter 4 ofStatistical Evidenceand on www.cmh.edu/stats/training/hand36.asp and www.cmh.edu/stats/training/hand72.asp. In this class you will learn how to:

- document examples where conflicts of interest have led to biased research results;
- list the important elements of a conflict of interest statement;
- identify measures to protect against fraudulent research.
October 2010:

Evidence Based Medicine: Publication bias in systematic overviews.Based largely on Chapter 5 ofStatistical Evidenceand on www.cmh.edu/stats/training/hand35.asp. In this class you will learn how to:

- recognize sources of heterogeneity in meta-analysis;
- explain graphical methods for identifying heterogeneity;
- understand methods to control for heterogeneity.
November 2010:

Evidence Based Medicine: Heterogeneity in systematic overviews.Based largely on Chapter 5 ofStatistical Evidenceand on www.cmh.edu/stats/training/hand35.asp. In this class you will learn how to:

- define publication bias;
- identify methods to control for publication bias;
- explain the ethical concerns with failure to publish and with duplicate publication.
December 2010:

Your first three steps in writing a research protocol.Based largely on www.cmh.edu/stats/training/hand42.asp. In this class you will learn how to:

- identify various research designs and their practical limitations;
- implement blinding and randomization in a research study;
- calculate an appropriate sample size;
- identify ethical issues associated with randomization and blinding.
January 2011:

Your first three steps in selecting a sample size.Based largely on www.pmean.com/09/AppropriateSampleSize.html. In this class you will learn how to:

- define a testable hypothesis;
- find an appropriate estimate of variation for your outcome measure;
- identify the minimum difference that still has clinical significance.
February 2011:

Your first three steps in data entry and documentation.Based largely on www.cmh.edu/stats/training/hand01.asp. In this class you will learn how to:

- structure your data so that is amenable for data analysis;
- add documentation to your data set;
- identify special problems with date values.
March 2011:

Your first three steps in a descriptive data analysis.Based largely on www.cmh.edu/stats/training/hand02.asp. In this class you will learn how to:

- distinguish between categorical and continuous variables;
- compute ranges and frequencies;
- examine relationships among variables.
April 2011:

Your first three steps in a linear regression analysis.Based largely on www.cmh.edu/stats/training/hand03.asp. In this class you will learn how to:

- interpret the slope and intercept in a linear regression model;
- compute a simple linear regression model;
- make statistical adjustments for covariates.
May 2011:

Your first three steps in a logistic regression analysis.Based largely on www.cmh.edu/stats/training/hand04.asp. In this class you will learn how to:

- compute and interpret simple odds ratios;
- relate the output of a logistic regression model to these odds ratios;
- examine the assumptions behind your logistic model.
June 2011:

Your first three steps in a survival data analysis.Based largely on www.cmh.edu/stats/training/hand05.asp. In this class you will learn how to:

- define censoring;
- apply the Kaplan-Meier estimate of the survival function;
- compare survival times using the log-rank test.