Summary - IPPCR Video and Handout Archive

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Take Home Hypothesis Testing• How to turn questions into hypotheses• Failing to reject the null hypothesisDOES NOT mean that the null is true• Every test has assumptions– A statistician can check all theassumptions– If the data does not meet the assumptionsthere are non-parametric versions of tests(see text)
Never “Accept” Anything• Reject the null hypothesis• Fail to reject the null hypothesis• Failing to reject the null hypothesis doesNOT mean the null (H 0 ) is true• Failing to reject the null means– Not enough evidence in your sample toreject the null hypothesis– In one sample saw what you saw
Page 2: Objectives• Review part of course
Page 6 and 7: Exam• Students will only have one
Page 8 and 9: OutlineExam information‣Take home
Page 10 and 11: Intervention Based ResearchSpectrum
Page 12 and 13: Types of Randomized Studies• Para
Page 14 and 15: Epidemiology• Study of the distri
Page 16 and 17: Non-Randomized• Can ONLY showAsso
Page 18 and 19: Random Example (Game 1)• Everybod
Page 20 and 21: Motivation Behind Randomization•
Page 22 and 23: Randomization Summary• Permuted b
Page 24 and 25: Intent to Treat vs. Completers• I
Page 26 and 27: Ways to Randomize• Standard ways:
Page 28 and 29: Types of Randomization• Simple•
Page 30: Statistical Inference• Inferences
Page 40 and 41: Tak e Home:V ocabulary• Null Hypo
Page 42 and 43: High ORDoes Not a Good Test Make•
Page 44 and 45: Estimates and P-V PV alues• Group
Page 49 and 50: Sample Size and Power
Page 51 and 52: Tak eAway• Study’s primary outc
Page 53 and 54: Tak e Home: N• Difference (effect
Page 55 and 56: If I cut my difference of interesti
Page 57 and 58: Define the OutcomeV ariable• What
Page 59 and 60: Kaplan Meier• One way to estimate
Page 61 and 62: Cox Model for Event Rates• Provid
Page 63 and 64: Prevalence vs. Incidence• “In t
Page 65 and 66: Effect Modification Link NEW• htt
Page 67 and 68: OutlineExam informationTake home me
Page 69 and 70: Logistic RegressionAssumptions• D
Page 71 and 72: Logistic Regression:Fundamental Que
Page 73 and 74: Statistics for Binary Data (2)• O
Page 75 and 76: Contingency TableCharacter-Presence
Page 77 and 78: Why We Debate theInterpretation•
Page 79 and 80: Difference vs. Ratio• Invasive br
Page 81 and 82: Odds Ratios andRelative Risk (Risk
Page 83 and 84: 2 Examples (KC Mercy)• Physician
Page 85 and 86: ExampleContinued Stopped TotalTreat
Page 87 and 88: What is Important• Which event ma
Page 89 and 90:
NNT (from pmean)• Daily low dose
Page 91 and 92:
Basic Recommendation• Somewhere,
Page 93 and 94:
Why do Statistician’s s Care?•
Page 95 and 96:
Analysis Follows DesignQuestions
Page 97 and 98:
Conclusion• Many needsMany needs
Page 99 and 100:
Analysis Follows DesignQuestions
Page 101:
Questions?
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Summary - IPPCR Video and Handout Archive

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