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teffects psmatch command  (STATA Corporation)


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    STATA Corporation teffects psmatch command
    Teffects Psmatch Command, supplied by STATA Corporation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/teffects+psmatch+command/teffects+psmatch+command/pm37422916-65-1-8
    Average 90 stars, based on 1 article reviews
    teffects psmatch command - by Bioz Stars, 2026-09
    90/100 stars

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    other:

    Article Title: Uric Acid and acute kidney injury in high-risk patients for developing Acute Kidney Injury undergoing cardiac surgery: a prospective multicenter study.
    Article Snippet: Objective: It is unclear whether elevated preoperative serum uric acid (SUA) plays a role in the development of cardiac surgery-associated acute kidney injury (CS-AKI).. We performed a cohort study to evaluate the impact of hyperuricemia on patients at high risk of this complication.. Design: Prospective multicentre cohort study.

    Article Title: Psychological resilience matters in the relationship between the decline in economic status and adults’ depression half a year after the outbreak of the COVID-19 pandemic
    Article Snippet: We used a developed package—teffects psmatch—available in Stata software, version 17.0, to estimate the average treatment effect on the treated (ATET).

    Article Title: Green transition and gender bias: An analysis of renewable energy generation companies in Latin America
    Article Snippet: This study analyzes how the energy transition might change gender bias in power-generating industries.. We employ a sample of 102 renewable energy generation companies from six countries in Latin America and the Caribbean: Bolivia, Chile, Costa Rica, Panama, Mexico, and Uruguay.. The analysis shows that renewable generation companies with the highest relative efficiency in the labor-capital ratio are those with the highest participation of women.

    Article Title: A practical guide to estimating treatment effects in patients with rheumatic diseases using real-world data.
    Article Snippet: Stata codes and with selected output for the average treatment effect by propensity score matching: teffects psmatch (das28_1) (treatment das28_0 age i.sex, logit), ate das28_1 Coefficient std. err. z P > z [95% conf. interval] ATE treatment (1 vs. 0) 0.041 0.193 0.21 0.831 − 0.338 0.421 The Stata command teffects psmatch conducts somewhat more complete matching with reused observations and provides the possibility of more than one match to each treatment observation.

    Article Title: Economics of widowhood mortality in adult women in India.
    Article Snippet: The economic consequence of widowhood on health is well-established, demonstrating that economic factors can significantly link with health outcomes, even the risk of mortality for widows.. However, empirical evidence is restricted only to developed countries.. Thus, this study assesses the role of economic factors (paid work, pension and household economic status) on the mortality of widows in broad age groups in India.

    Article Title: A practical guide to estimating treatment effects in patients with rheumatic diseases using real-world data.
    Article Snippet: The main estimation strategies are regression adjustment (e.g., Stata command teffects ra), inverse-probability weighting (e.g., Stata command teffects ipw), and matching (e.g., Stata commands teffects nnmatch, teffects psmatch and the user-developed command psmatch2).

    Article Title: How Does Tobacco Use Affect the Cognition of Older Adults? A Propensity Score Matching Analysis Based on a Large-Scale Survey.
    Article Snippet: Introduction: Tobacco is a well-established risk factor for cancer, but its association with other morbidities needs consideration.. The low-income and middle-income countries (LMICs) with unprecedented demographic transformation lack evidence on tobacco use and its impact on cognitive health.. Aims and Methods: Using a propensity score matching approach, we utilized data from the Longitudinal Ageing Study of India.



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