Figure 5.3b

Title:

Prevalence of past 30-day cigarette smoking (with 95% confidence band) for female and male high school students as a function of historical time: 1990 – 2017.

Syntax:

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%WeightedTVEM(data = smoking_risk,
Cluster = id,
Time = year_centered,
Dv = smk30day,
Dist = binary,
tvary_effect = int,
knots = 3 1,
weight = v5);

%WeightedTVEM(data=smoking_risk,
     cluster=id,
        time=year_centered,
          dv=smk30day,
        dist=logistic, 
tvary_effect=int male,
       knots=3 1,
      weight=v5);

data results.cig_male_overall;
  set tvem_plot_data;
  pfemale=exp(int)/(1+(exp(int))); 
  pfemale_U=exp(int_U)/(1+(exp(int_U)));
  pfemale_L=exp(int_L)/(1+(exp(int_L)));
  *effect of being male;
  pmale=exp(int+male)/(1+(exp(int+male)));
  pmale_U=exp(int_U+male_U)/(1+(exp(int_U+male_U)));
  pmale_L=exp(int_L+male_L)/(1+(exp(int_L+male_L)));
  *estimated odds ratios;
  OR=exp(male);
  OR_U=exp(male_U);
  OR_L=exp(male_L);
run;
proc export data=results.cig_male_overall
            dbms=xlsx
            outfile='C:\Users\admin_sxl194\Box\LAB - ADDICTION AND INNOVATIVE METHODS (AIM)\AIM Lab_Research projects\SPRINGER BOOK\Chp5_Historical\Results\cig_male_overall'
            replace;
run;

Equation:

\ln \left(\frac{P(C I G)}{1+P(C I G)}\right)=\beta_{0}(t)+\beta_{1}(t) M A L E_{i}

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Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences

Authors: Stephanie Lanza and Ashley Linden-Carmichael

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Reprinted by permission from Springer Nature: Generalized Time-Varying Effect Models for Binary and Count Outcomes by Stephanie T. Lanza and Ashley N. Linden-Carmichael, 2021.