Propensity Score in Complex Survey Contexts
Pre-workshop quiz for
based on the following pre-reading:
Austin, P. C. (2011). A tutorial and case study in propensity score analysis: an application to estimating the effect of in-hospital smoking cessation counseling on mortality. Multivariate behavioral research, 46(1), 119-151.
Respondent's name (optional)
How familiar are you with the propensity score analysis?
Not at all
How familiar are you with the complex survey data analysis (such as NHANES, BRFSS or CCHS)?
Not at all
What is the first step of a propensity score analysis (according to Austin, 2011)?
specify the propensity score model to estimate propensity scores
estimate the effect of treatment on outcomes using propensity score-matched sample
match treated and untreated subjects on the estimated propensity scores
compare the similarity of baseline characteristics between treated and untreated subjects in a the propensity score-matched sample
How did Austin (2011) estimate the propensity score?
He used a logistic regression model, where the treatment status was regressed on 33 baseline characteristics.
He fitted a modified the Cox proportional hazards model by using restricted cubic smoothing splines to model the relationship between continuous baseline covariates and the log-hazard of mortality.
He used a Cox proportional hazard model, where the outcome status was regressed on 33 baseline characteristics.
In Table 1 of Austin (2011), what balance diagnostic was used to compare the baseline characteristics of treated and untreated participants?
Standardized Difference of the Mean
logistic regression model
area under the receiver operating characteristic [ROC] curve
number needed to treat (NNT)
Which of the following approach is not a direct propensity score analysis technique?
Propensity Score Matching
Stratification on the Propensity Score
Inverse Probability of Treatment Weighting
Covariate adjustment using the propensity score
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