Essays about: "inverse probability treatment weighting"
Found 5 essays containing the words inverse probability treatment weighting.
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1. An Empirical Investigation of The Effect of Proxy Response and The Merits of Its Remedial Measures
University essay from Högskolan Dalarna/Institutionen för information och teknikAbstract : In the event of missing data, substitution of data from proxy sources are usually considered a very useful alternative when available to avoid the problem of missingness. Nonetheless, research has also shown that this approach often induces “response bias”. READ MORE
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2. The performance of inverse probability of treatment weighting and propensity score matching for estimating marginal hazard ratios
University essay from Uppsala universitet/Statistiska institutionenAbstract : Propensity score methods are increasingly being used to reduce the effect of measured confounders in observational research. In medicine, censored time-to-event data is common. READ MORE
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3. Improved estimation of the ATT from longitudinal data
University essay from Umeå universitet/StatistikAbstract : Our goal is to improve the estimation of the average treatment effect among treated (ATT) from longitudinal data. When the ATT is estimated at one time point (or separately at each), outcome-regression (OR), inverse probability weighting and doubly robust estimators can be used. READ MORE
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4. Cash is Queen - Impacts of conditional cash transfers on women’s empowerment
University essay from Lunds universitet/Nationalekonomiska institutionenAbstract : This thesis investigates the causal effects of the Peruvian conditional cash transfer (CCT) program, Juntos, on women’s empowerment defined along the psychological and familial dimensions. Usually, the main goal of CCTs is to reduce poverty. READ MORE
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5. Causal Inference in a 22 Factorial Design Using Generalized Propensity Score
University essay from Statistiska institutionenAbstract : When estimating causal effects, typically one binary treatment is evaluated at a time. This thesis aims to extend the causal inference framework using the potential outcomes scheme to a situation in which it is of interest to simultaneously estimate the causal effects of two treatments, as well as their interaction effect. READ MORE