02-15-02 Stats III

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1 Threats to the Validity of Hypothesis Testing: Confounding Are the Groups Alike at the Start of the Study? Scott Wetstone, M.D. Community Medicine and Health Care University of Connecticut School of Medicine

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2 Objectives The student should be able to: Define and recognize “confounding variables.” Define “unbalanced confounding variables” and explain how they threaten the validity of a study. List methods that deal with unbalanced confounding variables. Detect ‘obvious’ unbalanced confounding variables in research articles.

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3 Group Comparison Method Dependent Variable: Death Rate Independent Variable: Smoking Control Group Experimental Group Non-smokers Smokers P experimental Observed Group Difference P control r control r experimental

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4 Critical Assumption The members of each group are alike in all possible ways except for the ‘dosage’ of the independent variable.

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6 Example Statoma, a newly discovered form of brain neoplasm, has a 75% response rate when treated with standard chemotherapy. An investigator wanted to compare this standard therapy with two other treatment regimens: 1) the standard drug therapy plus radiation, and 2) a new drug. Both the new therapies were reported to have a small rate of impotency as a side effect as well as being potentially lethal in a very small number of cases. Patients from a Statoma clinic were allowed to choose which of the three treatment groups they entered.

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7 Response rates for the three treatments: standard treatment: 85% standard treatment plus radiation: 65% new drug: 50%

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8 Confounding Variable Another independent variable (not the primary target of the research study) that affects the value of the dependent (outcome) variable.

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9 Confounding Variables Almost always EXIST! …………………………… However, they do not necessarily threaten the validity of a research study.

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10 Unbalanced Confounding Variable When a group has a higher amount of the confounding variable than another group. This unbalanced confounding variable could be the cause of the observed group difference!

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20 Dealing with Confounding Variables Before group assignment Randomization (group assignment) Homogeneous subjects (inclusion & exclusion criteria) Related sample designs (stratification & matching) After group assignment Subgroup analysis Adjustment

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24 Detecting Unbalanced Confounders (Table 1) Inclusion of Potential Confounders (common sense & professional judgment) Screening & diagnostic tests for statistical significance Interval data – t test Count data – binomial & chi-square tests

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25 Demographic Characteristics Characteristic Placebo (n = 95) Control (n=105) AGE (yr) (std dev) 62.3 15.1 58.0 17.7 Sex (% male) 58 59 Weight (kg) 75.6 18.8 70.3 17.6 Race (% white) 73 62 * Differences between study groups were not significant.

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26 POWER () The ability to detect a true effect, IF it really exists Type II Error () Failure to detect a true effect, IF it really exists  = 1 - 

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27 Factors Affecting Power FACTOR p b a n ­ ­ ¯ NE s ¯ ­ ¯ NE | m1-m2 | ­ ­ ¯ NE a ­ ­ ¯ ­ Statistical test YES YES NE data type & dist YES YES NE

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28 Demographic Characteristics Characteristic Placebo (n = 95) Control (n=105) AGE (yr) (std dev) 62.3 15.1 58.0 17.7 Sex (% male) 58 59 Weight (kg) 75.6 18.8 70.3 17.6 Race (% white) 73 62 * Differences between study groups were not significant.

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29 Two Standard Error Rule

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30 Demographic Characteristics Characteristic Placebo (n = 95) Control (n=105) AGE (yr) (std dev) 62.3 15.1 58.0 17.7 Sex (% male) 58 59 Weight (kg) 75.6 18.8 70.3 17.6 Race (% white) 73 62 * Differences between study groups were not significant.

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38 Infant Behavior Feature Leboyer Group (28 Infants) Control Group (26 Infants) Activity during 1 st hour Time alert (min) (mean & range) Time crying (min) (mean & range) 40 (2-55) 6 (0-31) 27 (5-57) 7.5 (0-46) Brazelton Ridits (24 hr) (mean + S.E.M.) Interactive processes* Motor processes State control Response to stress 0.54 + 0.06 0.54 + 0.06 0.52 + 0.06 0.54 + 0.06 0.45 + 0.06 0.46 + 0.06 0.48 + 0.06 0.47 + 0.06

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39 Infant Behavior Feature Leboyer Group (28 Infants) Control Group (26 Infants) Brazelton Ridits (72 hr) (mean + S.E.M.) Interactive processes Motor processes State control Response to stress 0.56 + 0.06 0.58 + 0.06 0.54 + 0.06 0.57 + 0.06 0.53 + 0.06 0.50 + 0.06 0.49 + 0.06 0.59 + 0.06 Bayley Scales of Infant Development (mean + S.D.) Mental developmental index Physical developmental index 123.8 + 15.4 110.1 + 10.8 122.3 + 16.8 112.2 + 10.1

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40 Infant Behavior Feature Leboyer Group (28 Infants) Control Group (26 Infants) Activity during 1 st hour Time alert (min) (mean & range) Time crying (min) (mean & range) 40 (2-55) 6 (0-31) 27 (5-57) 7.5 (0-46) Brazelton Ridits (24 hr) (mean + S.E.M.) Interactive processes* Motor processes State control Response to stress 0.54 + 0.06 0.54 + 0.06 0.52 + 0.06 0.54 + 0.06 0.45 + 0.06 0.46 + 0.06 0.48 + 0.06 0.47 + 0.06

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41 Infant Behavior Feature Leboyer Group (28 Infants) Control Group (26 Infants) Brazelton Ridits (72 hr) (mean + S.E.M.) Interactive processes Motor processes State control Response to stress 0.56 + 0.06 0.58 + 0.06 0.54 + 0.06 0.57 + 0.06 0.53 + 0.06 0.50 + 0.06 0.49 + 0.06 0.59 + 0.06 Bayley Scales of Infant Development (mean + S.D.) Mental developmental index Physical developmental index 123.8 + 15.4 110.1 + 10.8 122.3 + 16.8 112.2 + 10.1

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44 Successes probability culm prob 0 0.00024 0.00024 1 0.00293 0.00317 2 0.01611 0.01929 3 0.05371 0.07300 4 0.12085 0.19385 5 0.19336 0.38721 6 0.22559 0.61279 7 0.19336 0.80615 8 0.12085 0.92700 9 0.05371 0.98071 10 0.01611 0.99683 11 0.00293 0.99976 12 0.00024 1.00000

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45 Demographic Characteristics Characteristic Placebo (n = 95) Control (n=105) AGE (yr) (std dev) 62.3 15.1 58.0 17.7 Sex (% male) 58 59 Weight (kg) 75.6 18.8 70.3 17.6 Race (% white) 73 62 * Differences between study groups were not significant.

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46 Demographic Characteristics Characteristic Placebo (n = 95) Control (n=105) Race (% white) ---- # white # non-white 73 ---- 70 25 62 ---- 65 40 * Differences between study groups were not significant.

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49 Shift in Placebo Group 2 whites  non-whites

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51 Summary The student should be able to: Define and recognize “confounding variables.” Define “unbalanced confounding variables” and explain how they threaten the validity of a study. List methods that deal with unbalanced confounding variables. Detect ‘obvious’ unbalanced confounding variables in research articles.

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