Hypothesis Tests | ScienceGate

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.

Download Full-text

HMM Sequential Hypothesis Tests for Intrusion Detection in MANETs Extended Abstract

10.21236/ada439785 ◽

2003 ◽

Cited By ~ 2

Author(s):

Alvaro A. Cardenas ◽

Vahid Ramezani ◽

John S. Baras

Keyword(s):

Intrusion Detection ◽

Hypothesis Tests ◽

Sequential Hypothesis

Download Full-text

The underlying structure of nonnested hypothesis tests

Biometrika ◽

10.1093/biomet/73.2.333 ◽

1986 ◽

Vol 73 (2) ◽

pp. 333-343 ◽

Cited By ~ 33

Author(s):

JOHN T. KENT

Keyword(s):

Underlying Structure ◽

Hypothesis Tests

Download Full-text

Exact Distribution-Free Hypothesis Tests for the Regression Function of Binary Classification via Conditional Kernel Mean Embeddings

IEEE Control Systems Letters ◽

10.1109/lcsys.2021.3087409 ◽

2021 ◽

pp. 1-1

Author(s):

Ambrus Tamas ◽

Balazs Csanad Csaji

Keyword(s):

Binary Classification ◽

Regression Function ◽

Exact Distribution ◽

Hypothesis Tests ◽

Distribution Free

Download Full-text

A Bayesian-Network-based Approach to Risk Analysis in Runway Excursions

Journal of Navigation ◽

10.1017/s0373463319000109 ◽

2019 ◽

Vol 72 (5) ◽

pp. 1121-1139 ◽

Cited By ~ 1

Author(s):

Fernando Calle-Alonso ◽

Carlos J. Pérez ◽

Eduardo S. Ayra

Keyword(s):

Risk Analysis ◽

Bayesian Network ◽

Exploratory Analysis ◽

Hypothesis Tests ◽

Aircraft Accidents ◽

Risk Scenarios ◽

Key Variables ◽

Expert Recommendations

Aircraft accidents are extremely rare in the aviation sector. However, their consequences can be very dramatic. One of the most important problems is runway excursions, when an aircraft exceeds the end (overrun) or the side (veer-off) of the runway. After performing exploratory analysis and hypothesis tests, a Bayesian-network-based approach was considered to provide information from risk scenarios involving landing procedures. The method was applied to a real database containing key variables related to landing operations on three runways. The objective was to analyse the effects over runway overrun excursions of failing to fulfil expert recommendations upon landing. For this purpose, the most influential variables were analysed statistically, and several scenarios were built, leading to a runway ranking based on the risk assessed.

Download Full-text