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\title{Addressing Treatment Switching Bias with G-methods: Exploring the Impact of Model Specification}
\author[1,2]{Amani Al Tawil\thanks{Correspondence: altawil@ibe.med.uni-muenchen.de}}
\author[3]{Sean McGrath}
\author[4]{Robin Ristl\thanks{Equally contributed}}
\author[1,2]{Ulrich Mansmann\textsuperscript{†}}
\affil[1]{Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, Ludwig-Maximilians-Universität München}
\affil[2]{Pettenkofer School of Public Health, Faculty of Medicine, Ludwig-Maximilians-Universität München}
\affil[3]{Department of Biostatistics, Harvard T.H. Chan School of Public Health}
\affil[4]{Center for Medical Data Science, Medical University of Vienna}

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\section*{\centering \LARGE Electronic Supplementary Material 5}
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\large \textbf{Number (\%) of bootstrap replicate failures}
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\caption{Number (\%) of bootstrap replicate failures}
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& & \multicolumn{3}{c}{\textbf{Number (\%) of bootstrap replicate failures}}\\
\cmidrule(lr){3-5}
\multicolumn{2}{c}{\textbf{Approach}} & \textbf{CoxPH} & \textbf{Pooled Logistic Regression} & \textbf{Kaplan-Meier}\\
\hline
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\multirow{4}{*}{ \justifying \textbf{Intention to Treat}} 
&  \justifying Unadjusted for baseline covariates  & 12 (1.2) & 12 (1.2)& 12 (1.2)\\
&  \justifying  Adjusted for strata at randomization* & 0  & 0  & NA \\
&  \justifying  Adjusted for baseline covariates*    & 0  & 0  & NA \\
&  \justifying  Marginal effect adjusted for baseline covariates & NE  &  0 & NA\\
\hline
\multirow{4}{*}{ \justifying \textbf{Per Protocol}} &  \justifying  Excluding switchers & 128 (12.8)& 128 (12.8)& 128 (12.8)\\
&  \justifying Censoring at switching & 157 (15.7) & 157 (15.7)& 157 (15.7) \\
&  \justifying Treatment as time-varying covariate  & 127 (12.7) & 127 (12.7) & 127 (12.7)\\
&  \justifying Inverse probability of censoring weights* & 14 (1.4) & 14 (1.4) & 14 (1.4)\\
&  \justifying Parametric g-formula\tnote{\ding{67}} & NE & 2 (0.4) & NE\\
\hline
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\begin{tablenotes}
%\item[\ding{61}] $95\%$ CI calculated using a non-parametric bootstrap procedure based on 1000 samples
%\item[\ding{67}] \justifying Reported CI calculated using a non-parametric bootstrap procedure based on 500 samples\\
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\item \justifying \textbf{Abbreviations}: CoxPH, cox proportional hazard; %HR, hazard ratio; dHR, discrete hazard ratio; cHR, cumulative hazard ratio; RR, risk ratio; 
CI, confidence interval; NE, not estimated; NA, not applicable
\item \justifying \textbf{*Strata at randomization}: presence or absence of baseline brain metastases and completion of at least one full cycle of chemotherapy for locally advanced or metastatic disease (yes or no)
\item \justifying \textbf{*Baseline covariates}: age, ECOG score, measurable intracranial CNS disease, race, sex, smoking history, strata at randomization, initial diagnosis stage, lung involvement at study entry and prior radiation therapy 
\item \justifying \textbf{*Inverse probability of censoring weight}: Estimates for the IPCW approach were estimated using a weighted pooled logistic regression model using the product of the two weights for LTFU/AC (specifications 4 in Table 4) and switching (specifications 4 in Table 5). 
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