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. 2010 Sep 11;111(1):145–153. doi: 10.1007/s00421-010-1633-1

Table 2.

Coefficients of the regression model for finish time

Effect Coefficient Standard error Coef/SE p
First time since 1985 (constant) 24.060 0.545 44.131 <0.001
Previous drop (constant) 18.490 1.399 13.216 <0.001
Finished previous start (constant) 24.160 0.561 43.030 <0.001
Relative performance at previous start (for those who finished the previous start) −1.725 0.310 −5.566 <0.001
Female 1.347 0.123 10.968 <0.001
One year greater age up to 38 years 0.043 0.015 2.840 0.005
One year greater age within 38–50-year interval 0.167 0.010 16.375 <0.001
One year greater age above 50 years 0.122 0.018 6.857 <0.001
Minimum ambient temperature (°C) 0.081 0.039 2.089 0.037
Finished WSER before 1986 −4.302 1.509 −2.851 0.004
Proportion of previous starts finished since 1986 −1.821 0.317 −5.750 <0.001
Finished WSER before 1986 × first time since 1985 −0.533 0.219 −2.436 0.0148
One year greater age up to 38 years × previous drop 0.139 0.036 3.836 <0.001
Relative performance at previous start × minimum ambient temperature (°C) 0.070 0.031 2.263 0.0236
Relative performance at previous start × proportion of previous starts finished since 1986 −2.198 0.894 −2.459 0.0139
Female × minimum ambient temperature (°C) −0.047 0.023 −2.047 0.0407
One year greater age up to 38 years × finished WSER before 1986 0.083 0.040 2.088 0.0368
One year greater age within 38–50-year interval × proportion of previous starts finished since 1986 0.099 0.028 3.522 <0.001
One year greater age above 50 years × finished WSER before 1986 0.080 0.033 2.408 0.016

The constants apply to the three categories into which all finishes are sorted each year. Subsequent coefficients apply equally to all finishes except where noted explicitly. Positive coefficients increase and negative coefficients decrease the average finish time. Specifically, the coefficient for a dichotomous variable (female or finished WSER before 1986) is added directly to the average finish time. On the other hand, the coefficient for a quantitative variable is multiplied by a difference in the variable’s value and this product is added to the average finish time