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2009 Joint Statistical Meetings Washington, DC August 1-6, 2009 Interpreting Differential Effects in Light of Fundamental Statistical Tendencies . James P. Scanlan Attorney at Law Washington, DC, USA firstname.lastname@example.org Oral at http://www.jpscanlan.com/images/JSM_2009_ORAL.pdf. Summary .
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2009 Joint Statistical Meetings Washington, DC August 1-6, 2009Interpreting Differential Effects in Light of Fundamental Statistical Tendencies
James P. Scanlan
Attorney at Law
Washington, DC, USA
Oral at http://www.jpscanlan.com/images/JSM_2009_ORAL.pdf
1. Factors that similarly affect two groups with different baseline rates of an outcome will tend to show a larger proportionate effect on the outcome for the group with the lower base rate but a larger proportionate effect on the opposite outcome for the other group
2. True subgroup effects can only be identified by determining the degree to which a factor shifts each group’s risk distribution
There exists a tendency to regard it as somehow normal that a factor that similarly affects two groups’ susceptibilities to an outcome will cause the same proportionate change in the outcome rates for each group and to regard anything else as a differential effect (subgroup effect, interaction)
Fig 3. Ratios of (1) Bl Rate of Falling below Various Income Levels to Wh Rate of Falling below Level and (2) Wh Rate of Falling above Level to Bl Rate of Falling above Level
Fig. 4. Ratio of (1) Bl to Wh Rate of Falling above Various SBP Levels and (2) Wh to Bl Rate of Falling below the Level (NHANES 1999-2000, 2001-2002, Men 45-64)
Estimated effect size (EES) = estimated difference, in terms of percentage of a standard deviation, between means of hypothesized underlying, continuously-scaled normal distributions of factors associated with experiencing an outcome, derived from outcome rates of each group (see JSM 2008 and Solutions and Solutions Database tabs on jpscanlan.com)
Period Yr 1 Yr 2
AG Rate 60% 42%
DG Rate 77% 60%
Measures of Difference Change Direction
AdvRatio 1.16 1.43 Increase
FavRatio 1.74 1.45 Decrease
EES (z).50.47 Decrease
Table 3. Comparison of Effects of Hypertension Control on Heart Attack Risk of Women and Men with Similar Risk Factor Profiles (A65,TC300,HDL50,NS, NM) (Perspective 1)
Table 4. Comparison of Gender Differences in Heart Attack Risk for Women and Men with Similar Risk Factor Profiles, by with and without Hypertension Control (A65,TC300,HDL50,NS, NM) (Perspective 2)
Table 6. Comparison of Effects of Increasing Smoking from <11 to >29 Cig Per Day on Whites and Blacks (Haimon NEJM 2006) (Perspective 1) (cor. 9/13/10)
Table 8. Comparison of Age Differences in Mortality Among Patients Treated and Not Treated with Beta Blockers (Gottlieb NEJM 1998) (Perspective 2)