scholarly journals Point and Interval Estimators of an Indirect Effect for a Binary Outcome

2021 ◽  
pp. 279-295
Author(s):  
Hyung Rock LEE ◽  
Jaeyun SUNG ◽  
Sunbok LEE
Keyword(s):  
Indirect Effect ◽  
Binary Outcome ◽  
Interval Estimators

scholarly journals Estimating the natural indirect effect and the mediation proportion via the product method

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chao Cheng ◽  
Donna Spiegelman ◽  
Fan Li
Keyword(s):  
Sample Size ◽  
Indirect Effect ◽  
Mediation Analysis ◽  
Variance Estimation ◽  
Delta Method ◽  
Binary Outcome ◽  
Finite Sample ◽  
Data Types ◽  
Product Method ◽  
Interval Estimator

Abstract Background The natural indirect effect (NIE) and mediation proportion (MP) are two measures of primary interest in mediation analysis. The standard approach for mediation analysis is through the product method, which involves a model for the outcome conditional on the mediator and exposure and another model describing the exposure–mediator relationship. The purpose of this article is to comprehensively develop and investigate the finite-sample performance of NIE and MP estimators via the product method. Methods With four common data types with a continuous/binary outcome and a continuous/binary mediator, we propose closed-form interval estimators for NIE and MP via the theory of multivariate delta method, and evaluate its empirical performance relative to the bootstrap approach. In addition, we have observed that the rare outcome assumption is frequently invoked to approximate the NIE and MP with a binary outcome, although this approximation may lead to non-negligible bias when the outcome is common. We therefore introduce the exact expressions for NIE and MP with a binary outcome without the rare outcome assumption and compare its performance with the approximate estimators. Results Simulation studies suggest that the proposed interval estimator provides satisfactory coverage when the sample size ≥500 for the scenarios with a continuous outcome and sample size ≥20,000 and number of cases ≥500 for the scenarios with a binary outcome. In the binary outcome scenarios, the approximate estimators based on the rare outcome assumption worked well when outcome prevalence less than 5% but could lead to substantial bias when the outcome is common; in contrast, the exact estimators always perform well under all outcome prevalences considered. Conclusions Under samples sizes commonly encountered in epidemiology and public health research, the proposed interval estimator is valid for constructing confidence interval. For a binary outcome, the exact estimator without the rare outcome assumption is more robust and stable to estimate NIE and MP. An R package is developed to implement the methods for point and variance estimation discussed in this paper.

Indirect Effect of Job Burnout on Job Engagement

2013 ◽  
Author(s):  
Kotaro Shoji ◽  
Emily Luther ◽  
Roman Cieslak ◽  
Ewelina Smoktunowicz ◽  
Charles C. Benight
Keyword(s):  
Indirect Effect ◽  
Job Burnout ◽  
Job Engagement

Determining the Most Valuable Clinical Variables : a Stepwise Multiple Logistic Regression Program

1980 ◽  
Vol 19 (01) ◽  
pp. 42-49 ◽  
Author(s):  
B. W. Brown ◽  
C. Engelhard ◽  
J. Haipern ◽  
J. F. Fries ◽  
L. S. Coles
Keyword(s):  
Logistic Regression ◽  
Predictor Variable ◽  
Clinical Problem ◽  
Relevant Information ◽  
Stepwise Logistic Regression ◽  
Multiple Logistic Regression ◽  
Binary Outcome ◽  
Medical Problems ◽  
Valuable Predictor ◽  
Data Banks

In solving a clinical problem of diagnosis, prognosis, or treatment choice, a physician must select from among a large group of possible tests. In general, an ordering exists specifying which tests are most valuable in providing relevant information concerning the problem on hand. The computer program package to be described (MW) extracts appropriate data from the ARAMIS data banks and then analyzes the data by stepwise logistic regression. A binary outcome (diagnosis, prognostic event, or treatment response) is sequentially associated with possible tests, and the most powerful combination of tests is identified. For example, the most valuable predictor variable of early mortality in SLE is proteinuria, followed sequentially by anemia and absence of arthritis. Experience with these techniques suggests : 1. optimal certainty is usually reached after only three or four tests; 2. several different test sequences may lead to the same level of certainty; 3. diagnosis may usually be ascertained with greater certainty than prognosis; 4. many medical problems contain considerable non-reducible uncertainty; 5. a relatively small group of tests are typically found among the most powerful; 6. results are consistent across several patient populations; 7. results are largely independent of the particular statistic employed. These observations suggest strategies for maximizing information while minimizing risk and expense.

Indirect effect of catecholamines on development of insulin resistance in skeletal muscle from diabetic rats

Diabetes ◽  
1989 ◽  
Vol 38 (7) ◽  
pp. 906-910 ◽  
Author(s):  
M. Bostrom ◽  
Z. Nie ◽  
G. Goertz ◽  
J. Henriksson ◽  
H. Wallberg-Henriksson
Keyword(s):  
Insulin Resistance ◽  
Skeletal Muscle ◽  
Indirect Effect ◽  
Diabetic Rats

Faktor-Faktor yang Mempengaruhi Minat Beli Produk Makanan Olahan Halal pada Konsumen

2018 ◽  
Vol 8 (3) ◽  
pp. 250
Author(s):  
Saniatun Nurhasah ◽  
Jono M Munandar ◽  
Muhammad Syamsun
Keyword(s):  
Food Safety ◽  
Direct Effect ◽  
Indirect Effect ◽  
Purchase Intention ◽  
Brand Image ◽  
Perceived Value ◽  
Perceived Quality ◽  
Market Potential ◽  
Purchasing Intention ◽  
Positive Direct

<p><em>ABSTRACT</em></p><p><em>Indonesia is one of the largest Moslem population countries in the world. It leads to the increasing of halal product demand in Indonesia. The awareness to consume halal product becomes a large market potential for producers to produce their halal products. Nowadays, halal is not only purely about religion matter, but also about business and trade. The objective of this study is to investigate the factors affecting customers on purchasing halal buying interest on processed food. We use a purposive sampling method with 109 respondents who are customers of the supermarkets and minimarkets in Bogor City/District, Indonesia. While data analysis is done by SEM-PLS method, this study uses brand image, perceived quality, perceived value, halal certification, health reason, halal awareness, and halal marketing as the factors which are affecting the halal purchase intention of the customers. The result showed that health reason, halal awareness, and perceived value have a significant and positive direct effect on purchasing intention. Halal marketing also shows a significant and positive effect on purchasing intention. While halal marketing shows a negative and significant effect on purchasing intention. The food safety, halal certification, brand image, and perceived quality show the same effect which has no direct effect on purchasing intention. Furthermore, food safety has an indirect effect on purchasing intention through health reason. Halal certification has an indirect effect on minat beli through brand image variable. Meanwhile, brand image and perceived quality have an indirect effect through perceived value variable on purchasing intention.</em></p><p><em><br /></em></p><p>ABSTRAK</p><p>Indonesia adalah salah satu negara dengan populasi Muslim terbesar di dunia. Hal ini menyebabkan meningkatnya permintaan produk halal di Indonesia. Kesadaran untuk mengkonsumsi produk halal menjadi potensi pasar yang besar bagi produsen untuk memproduksi produk halal mereka. Saat ini, halal tidak hanya murni soal agama, tapi juga soal bisnis dan perdagangan. Tujuan dari penelitian ini adalah untuk mengetahui faktor-faktor yang mempengaruhi minat pelanggan dalam membeli pada makanan olahan halal. Kami menggunakan metode voluntery sampling dengan 109 responden yang merupakan pelanggan supermarket dan minimarket di Kota/Kabupaten Bogor, Indonesia. Sedangkan analisis data dilakukan dengan metode SEM-PLS. Penelitian ini menggunakan citra merek, persepsi kualitas, persepsi nilai, sertifikasi halal, kesehatan, kesadaran halal, dan Pemasaran halal sebagai faktor yang mempengaruhi niat pembelian halal pelanggan. Hasil penelitian menunjukkan bahwa kesadaran halal, alasan kesehatan, dan persepsi nilai berpengaruh positif dan signifikan terhadap niat beli. Pemasaran halal juga menunjukkan efek positif dan signifikan terhadap niat beli. Sedangkan pemasaran halal menunjukkan efek negatif dan signifikan terhadap niat beli. Keamanan pangan, sertifikasi halal, citra merek, dan kualitas yang dirasakan menunjukkan efek yang sama yang tidak berpengaruh langsung pada niat beli. Selanjutnya, keamanan pangan berpengaruh tidak langsung terhadap niat beli melalui alasan kesehatan. Sertifikasi halal memiliki efek tidak langsung terhadap niat beli melalui variabel citra merek. Sedangkan citra merek dan persepsi kualitasmemiliki pengaruh tidak langsung melalui persepsi nilai variable terhadap niat beli.</p>

Two-Condition Within-Participant Statistical Mediation Analysis: A Path-Analytic Framework

2019 ◽  
Author(s):  
Amanda Kay Montoya ◽  
Andrew F. Hayes
Keyword(s):  
Confidence Intervals ◽  
Indirect Effect ◽  
Mediation Analysis ◽  
Analytic Approach ◽  
Analytic Framework ◽  
Hypothesis Tests ◽  
Bootstrap Confidence Intervals ◽  
Complex Models ◽  
Path Analytic ◽  
Statistical Mediation Analysis

Researchers interested in testing mediation often use designs where participants are measured on a dependent variable Y and a mediator M in both of two different circumstances. The dominant approach to assessing mediation in such a design, proposed by Judd, Kenny, and McClelland (2001), relies on a series of hypothesis tests about components of the mediation model and is not based on an estimate of or formal inference about the indirect effect. In this paper we recast Judd et al.’s approach in the path-analytic framework that is now commonly used in between-participant mediation analysis. By so doing, it is apparent how to estimate the indirect effect of a within-participant manipulation on some outcome through a mediator as the product of paths of influence. This path analytic approach eliminates the need for discrete hypothesis tests about components of the model to support a claim of mediation, as Judd et al’s method requires, because it relies only on an inference about the product of paths— the indirect effect. We generalize methods of inference for the indirect effect widely used in between-participant designs to this within-participant version of mediation analysis, including bootstrap confidence intervals and Monte Carlo confidence intervals. Using this path analytic approach, we extend the method to models with multiple mediators operating in parallel and serially and discuss the comparison of indirect effects in these more complex models. We offer macros and code for SPSS, SAS, and Mplus that conduct these analyses.

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