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We present the coefficients from this model in Tables 5 and 6.
As a partial test of this hypothesis, we control for both region of birth and occupation in the last specifications of the model in Tables 9 and 10.
Therefore, it is not surprising that, as shown in our second model in Tables 2 and 3, numeracy was highly related to the highest level of education, explaining 29% of the variance.
As shown in the first model in Tables 2 and 3, the highest level of education was substantially related to personality, which together with the control variables explained 8% of the overall variance.
Least square probabilities of exercise and cohort effects (change per year), based on the model in Tables 3 and 4 adjusted for BMI, education, and self-reported health status, are shown in Tables 5 (men) and 6 (women).
Adjusted proportions of exercise and birth cohort trends (change per birth year), as well as age trends (change per year), based on the adjusted model in Tables 3 and 4 (adjusted for educational level, BMI, and self-reported health status) are shown in Table 5 (men) and 6 (women).> -wrap-foot>> -wraPlaintextlain text, 1988/89; bold, 1996/97; italics, 2004/05.
Similar(53)
Once again, Table 5 proves all the results of the Cox model in Table 4.
The rigidity model we used is calculated using the 1D model in Table 1.
The models are similar to the first model in Table 3.
See the description and definition of the variables used in the model in Table 1.
We present the results for the double threshold model in Table 6.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com