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Showing 1 to 9 of 9 for “"Propensity score analysis"”.
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Analyzing Electricity Use of Low Income Weatherization Program Participants Using Propensity Score Analysis and a Hierarchical Linear Growth Model
<p>This evaluation utilized propensity score matching methods and a longitudinal hierarchical linear growth model to determine the effect of residential energy efficiency upgrade(s) on household electricity use for the low-income community over the course of a year in the City and County of Denver, …
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The effect of child disability/delay status and functional abilities on father involvement: an application of propensity score analysis
… that do not provide estimates of causal effects. Propensity score analysis was used to estimate the causal effect of child disability/delay status on father routine caregiving, literacy, play, and responsive caregiving involvement. The association between functional abilities and father …
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High flow nasal oxygen versus mechanical ventilation as initial respirator support in severe COVID-19 ARDS at Groote Schuur Hospital : a propensity score analysis
… first” strategy. METHODS: This was a secondary analysis of two propsective cohort studies conducted during the COVID first wave at Groote Schuur Hospital. Propensity score matching was used to compare outcomes between HFNO as initial ventilation strategy and MV as first-line therapy. Eligible …
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Toward Nonparametric Propensity Score Estimation With Guaranteed Covariate Balance
… and biased treatment effect inference. The propensity score </em><em>(PS) has been widely used to adjust this covariate imbalance in observational data. However, </em><em>the propensity score analysis methods rely on a correctly specified parametric PS </em><em>model. When the model is …
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Statistical methods for outcome misclassification adjustment in causal inference and spatial classification.
… In the first work, we describe a Bayesian propensity score analysis to estimate the causal effect in observational studies with misclassified multinomial outcomes. To adjust the effect of misclassification, the informative Dirichlet priors are specified based on previous studies. Taking …
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Effect of renal replacement therapy on acute kidney injury in sepsis patients
… did not. Multivariate logistic regression and propensity score analysis were utilized to evaluate the treatment effect on mortality. The patients who underwent RRT had a significantly better outcome than those who did not (odds ratio = 0.260465, 95% confidence interval = 0.211568 to 0.320664, …
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Exploring Ethnocultural Differences in Distress of Newly Arrived Refugees During Early Resettlement: A Mixed Methods Dissertation
… every 3 months for 1 year, three approaches to propensity score analysis were performed with risk set matching on balancing time-varying covariates across treatment conditions at each time point. Subsequently, a three-way factorial ANOVA was conducted to examine mean differences in distress …
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Examining Immigrant Experiences in Asset Building: Implications for Asset-Based Policies
… advanced statistical models—logistic regression, propensity score analysis, and hierarchical modeling, this dissertation comprises three empirical papers investigating immigrants’ settlement, legal status, financial access, and wealth building, with analyses extending to the second generation. The …
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The effectiveness of pre-course and concurrent course interventions on at-risk college physics students' mechanics performance
… of risk were identified by logistic regression analysis on collected measures of prior education, national exam scores, university diagnostic scores, as well as demographic and socio-economic information. The study had a quasi-experimental, posttest only, non-equivalent control group design, …