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Sports Medicine Example. Background Does Sports Med Fellowship have an impact? Study Design –Compare people with fellowship to those without on ABFM exams.

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Presentation on theme: "Sports Medicine Example. Background Does Sports Med Fellowship have an impact? Study Design –Compare people with fellowship to those without on ABFM exams."— Presentation transcript:

1 Sports Medicine Example

2 Background Does Sports Med Fellowship have an impact? Study Design –Compare people with fellowship to those without on ABFM exams –Choose target content items as DV, other items as covariate.

3 A Word of Warning ANCOVA –Assign to treatment –Measured category Covariate can either increase power of test for categorical variable or destroy it

4 Data Collection Family Med exams –Item types Judges Item selection –Item sums Nmsk FM Fellowship

5 Distribution of Criterion Histogram # Boxplot 13.25+** 65 |. |.**** 156 |. |.********* 400 |. |.******************** 941 |. |.************************************ 1764 +-----+. | |.************************************************ 2334 *-----*. | + | 7.25+********************************************** 2240 | |. | |.******************************* 1494 +-----+. |.***************** 786 |. |.******* 319 |. |.** 84 |. |.* 21 |. 1.25+* 2 0 ----+----+----+----+----+----+----+----+----+--- * may represent up to 49 counts M=7.66, SD=1.83

6 Distribution of Covariate Histogram # Boxplot 227.5+* 2 0..* 19 |.**** 139 |.************* 441 | 202.5+************************** 909 |.****************************************** 1461 +-----+.************************************************ 1669 | |.************************************************ 1649 *--+--*.******************************************* 1494 | | 177.5+********************************* 1140 +-----+.*********************** 778 |.************* 448 |.******* 220 |.**** 126 | 152.5+** 50 0.* 28 0.* 16 0.* 2 0.* 4 0 127.5+* 1 *.* 1 *.* 3 *.* 4 *. 102.5+* 2 * ----+----+----+----+----+----+----+----+----+--- * may represent up to 35 counts M=186.63, SD=12.39

7 Distribution of Categorical Variable The FREQ Procedure Cumulative Cumulative fellow Frequency Percent Frequency Percent ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ 0 8896 83.88 8896 83.88 1 1710 16.12 10606 100.00

8 Correlations Pearson Correlation Coefficients, N = 10606 Prob > |r| under H0: Rho=0 nmsk fellow fm nmsk 1.00000 0.07397 0.30741 <.0001 <.0001 fellow 0.07397 1.00000 0.04147 <.0001 <.0001 fm 0.30741 0.04147 1.00000 <.0001 <.0001

9 ANCOVA Model 1 Dependent Variable: nmsk Sum of Source DF Squares Mean Square F Value Pr > F Model 3 3479.97692 1159.99231 385.81 <.0001 Error 10602 31876.67525 3.00667 Corrected Total 10605 35356.65218 R-Square Coeff Var Root MSE nmsk Mean 0.098425 22.64258 1.733974 7.658024 Standard Parameter Estimate Error t Value Pr > |t| Intercept -0.923637117 0.27487627 -3.36 0.0008 fellow 1.325887396 0.72536793 1.83 0.0676 fm 0.045720017 0.00147132 31.07 <.0001 fellow*fm -0.005444525 0.00385886 -1.41 0.1583

10 ANCOVA Model 2 Dependent Variable: nmsk Sum of Source DF Squares Mean Square F Value Pr > F Model 2 3473.99160 1736.99580 577.66 <.0001 Error 10603 31882.66057 3.00695 Corrected Total 10605 35356.65218 R-Square Coeff Var Root MSE nmsk Mean 0.098256 22.64364 1.734055 7.658024 Standard Parameter Estimate Error t Value Pr > |t| Intercept -.7760964638 0.25422026 -3.05 0.0023 fellow 0.3044987045 0.04582654 6.64 <.0001 fm 0.0449285119 0.00136023 33.03 <.0001

11 Graph of Result

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