scholarly journals Estimating General Parameters from Non-Probability Surveys Using Propensity Score Adjustment

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 2096
Author(s):  
Luis Castro-Martín ◽  
María del Mar Rueda ◽  
Ramón Ferri-García
Keyword(s):  
Propensity Score ◽  
Estimation Methods ◽  
Auxiliary Variables ◽  
Probability Sample ◽  
Inequality Measures ◽  
World Survey ◽  
Rigorous Framework ◽  
General Parameter ◽  
Using Data ◽  
Propensity Score Adjustment

This study introduces a general framework on inference for a general parameter using nonprobability survey data when a probability sample with auxiliary variables, common to both samples, is available. The proposed framework covers parameters from inequality measures and distribution function estimates but the scope of the paper is broader. We develop a rigorous framework for general parameter estimation by solving survey weighted estimating equations which involve propensity score estimation for units in the non-probability sample. This development includes the expression of the variance estimator, as well as some alternatives which are discussed under the proposed framework. We carried a simulation study using data from a real-world survey, on which the application of the estimation methods showed the effectiveness of the proposed design-based inference on several general parameters.

scholarly journals Distance-Based Estimation Methods for Models for Discrete and Mixed-Scale Data

Entropy ◽  
2021 ◽  
Vol 23 (1) ◽  
pp. 107
Author(s):  
Elisavet M. Sofikitou ◽  
Ray Liu ◽  
Huipei Wang ◽  
Marianthi Markatou
Keyword(s):  
Data Model ◽  
Null Hypothesis ◽  
Model Misspecification ◽  
Asymptotic Properties ◽  
Estimation Methods ◽  
Measurement Scale ◽  
Interval Scale ◽  
Pearson Residuals ◽  
Using Data ◽  
Scale Data

Pearson residuals aid the task of identifying model misspecification because they compare the estimated, using data, model with the model assumed under the null hypothesis. We present different formulations of the Pearson residual system that account for the measurement scale of the data and study their properties. We further concentrate on the case of mixed-scale data, that is, data measured in both categorical and interval scale. We study the asymptotic properties and the robustness of minimum disparity estimators obtained in the case of mixed-scale data and exemplify the performance of the methods via simulation.

What drives housing prices, rent and new construction in China

2017 ◽  
Vol 10 (5) ◽  
pp. 662-686
Author(s):  
Dimitrios Staikos ◽  
Wenjun Xue
Keyword(s):  
Real Estate ◽  
Empirical Test ◽  
Housing Prices ◽  
Panel Cointegration ◽  
Real Estate Market ◽  
Estimation Methods ◽  
Content Type ◽  
New Construction ◽  
Using Data ◽  
First Time

Purpose With this paper, the authors aim to investigate the drivers behind three of the most important aspects of the Chinese real estate market, housing prices, housing rent and new construction. At the same time, the authors perform a comprehensive empirical test of the popular 4-quadrant model by Wheaton and DiPasquale. Design/methodology/approach In this paper, the authors utilize panel cointegration estimation methods and data from 35 Chinese metropolitan areas. Findings The results indicate that the 4-quadrant model is well suited to explain the determinants of housing prices. However, the same is not true regarding housing rent and new construction suggesting a more complex theoretical framework may be required for a well-rounded explanation of real estate markets. Originality/value It is the first time that panel data are used to estimate rent and new construction for China. Also, it is the first time a comprehensive test of the Wheaton and DiPasquale 4-quadrant model is performed using data from China.

scholarly journals Causal inference with multiple concurrent medications: A comparison of methods and an application in multidrug-resistant tuberculosis

2018 ◽  
Vol 28 (12) ◽  
pp. 3534-3549 ◽  
Author(s):  
Arman Alam Siddique ◽  
Mireille E Schnitzer ◽  
Asma Bahamyirou ◽  
Guanbo Wang ◽  
Timothy H Holtz ◽  
...  
Keyword(s):  
Propensity Score ◽  
Simulation Study ◽  
Antimicrobial Agents ◽  
Treatment Success ◽  
Likelihood Estimation ◽  
Multidrug Resistant ◽  
Patient Treatment ◽  
Resistant Tuberculosis ◽  
Multidrug Resistant Tuberculosis ◽  
Propensity Score Adjustment

This paper investigates different approaches for causal estimation under multiple concurrent medications. Our parameter of interest is the marginal mean counterfactual outcome under different combinations of medications. We explore parametric and non-parametric methods to estimate the generalized propensity score. We then apply three causal estimation approaches (inverse probability of treatment weighting, propensity score adjustment, and targeted maximum likelihood estimation) to estimate the causal parameter of interest. Focusing on the estimation of the expected outcome under the most prevalent regimens, we compare the results obtained using these methods in a simulation study with four potentially concurrent medications. We perform a second simulation study in which some combinations of medications may occur rarely or not occur at all in the dataset. Finally, we apply the methods explored to contrast the probability of patient treatment success for the most prevalent regimens of antimicrobial agents for patients with multidrug-resistant pulmonary tuberculosis.

scholarly journals Impact Evaluation of Raskin Program using Matching Method: Case of IFLS 5

JEJAK ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 207-223
Author(s):  
Endiarjati Dewandaru Sadono
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Family Life ◽  
Household Income ◽  
Impact Evaluation ◽  
Matching Method ◽  
Indonesia Family Life Survey ◽  
Small Benefit ◽  
Using Data ◽  
The Impact

Beras untuk Keluarga Miskin (RASKIN) program has been applied since 1998 and has been renamed as Beras Sejahtera (RASTRA) in early 2017, but their effectiveness is still debatable. This study tries to evaluate the impact of RASKIN program on household income. Using data from 3,745 households in Indonesia Family Life Survey (IFLS) 5 that has been estimated using propensity score matching, this study has identified precisely that RASKIN program has a negative and significant effect on household income. This happens because the benefits that reveived by Rumah Tangga Sasaran (RTS) are very small. The small benefit is affected by the amount of rice received, frequency and price that have been paid to get RASKIN is not in accordance with the guidelines. The result of this study is along with previous studies, where the amount and price of rice that distributed through RASKIN program is not exactly correct. Therefore, there must be a change in program format, not just renaming from RASKIN to RASTRA only.

scholarly journals Prognostic impact of pelvic and para-aortic lymphadenectomy on clinically-apparent stage I primary mucinous epithelial ovarian carcinoma: a multi-institutional study with propensity score-weighted analysis

2019 ◽  
Author(s):  
Masato Yoshihara ◽  
Hiroaki Kajiyama ◽  
Satoshi Tamauchi ◽  
Shohei Iyoshi ◽  
Akira Yokoi ◽  
...  
Keyword(s):  
Lymph Node ◽  
Propensity Score ◽  
Ovarian Carcinoma ◽  
Pelvic Lymphadenectomy ◽  
Epithelial Ovarian Carcinoma ◽  
Stage I ◽  
Therapeutic Effects ◽  
Prognostic Impact ◽  
Pathological Review ◽  
Using Data

Abstract Background The exact impact of full-staging lymphadenectomy on patients with primary mucinous epithelial ovarian carcinoma confined to the ovary is still unclear. In this study, we investigated the prognostic impact of lymphadenectomy covering both pelvic and para-aortic lymph nodes in patients with clinically-apparent stage I mucinous epithelial ovarian carcinoma, using data from multi-institutions under a central pathological review system and analyses with a propensity score-based method. Methods We conducted a regional multi-institutional retrospective study between 1986 and 2017. Among 4730 patients with malignant ovarian tumors, a total of 186 women with mucinous epithelial ovarian carcinoma were eligible. We evaluated differences in survival outcomes between patients with both pelvic and para-aortic lymphadenectomy and those with only pelvic lymphadenectomy and/or clinical lymph node evaluation. To analyze the therapeutic effects, the baseline imbalance between patients with both pelvic and para-aortic lymphadenectomy and others was adjusted with an inverse probability of treatment weighting using propensity score involving independent clinical variables. Results Fifty-five patients received both pelvic and para-aortic lymphadenectomy. With PS-based adjustment, both pelvic and para-aortic lymphadenectomy did not have additive effects regarding overall survival (P = 0.696) and recurrence-free survival (P = 0.978). Multivariate analysis similarly showed no significant impact of both pelvic and para-aortic lymphadenectomy on their prognosis. Conclusions The effect of pelvic and para-aortic lymphadenectomy is limited for clinically-apparent stage I primary mucinous epithelial ovarian carcinoma as long as full peritoneal and clinical lymph node evaluations are conducted. The results of this study should be used as the basis for additional studies, including prospective trials.

scholarly journals It’s Still about Race: Peremptory Challenge Use on Black Prospective Jurors

2019 ◽  
Vol 57 (1) ◽  
pp. 3-30 ◽  
Author(s):  
Whitney DeCamp ◽  
Elise DeCamp
Keyword(s):  
Propensity Score ◽  
Propensity Score Matching ◽  
Racial Discrimination ◽  
Racial Differences ◽  
Jury Selection ◽  
Racially Diverse ◽  
Criminal Trials ◽  
Peremptory Challenge ◽  
Using Data

Objectives: The use of race as a motive for excluding individuals from serving on juries in American criminal trials is unconstitutional. Nevertheless, Black individuals remain substantially more likely than others to be removed during jury selection through peremptory challenges. This study tests whether and to what extent there is a racial effect on peremptory challenge use by the prosecution or the defense. Method: Using data from 2,542 venire members in Mississippi, propensity score matching is used to examine racial differences in jury selection by comparing Black venire members to similarly situated White venire member counterparts. Results: Findings suggest that Black venire members are 4.51 times as likely to be excluded from a jury due to peremptory challenges from the prosecution in comparison to White venire members. Conversely, White venire members are 4.21 times as likely to be excluded through peremptory challenges by the defense in comparison to Black venire members. Conclusions: After controlling for all observed variables, there remain significant differences between White and Black venire members, suggesting racial discrimination by both the prosecution and the defense in peremptory challenge usage. Black individuals are more likely to be excluded from juries through these effects, resulting in less racially diverse juries.

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