Analyzing Associations Between Anxiety and Premature Ejaculation Using Longitudinal Data and Structural Equation Modeling

Daniel Ventus

doi:10.4135/9781526449498

Analyzing Associations Between Anxiety and Premature Ejaculation Using Longitudinal Data and Structural Equation Modeling

Daniel Ventus

Psychology

Research output: Chapter in Book/Conference proceeding › Chapter › Professional

Abstract

As part of my PhD research project, I was interested in what causes premature ejaculation. This case study presents analyses on possible causal associations between premature ejaculation and anxiety, as well as sexual distress and depression. The statistical method, structural equation modeling, is introduced and applied, as is the concept of latent variables. The results showed no long-term associations between the study variables, and possible interpretations of this result are presented. Pros and cons of using a previously collected data set are discussed.

Original language	Undefined/Unknown
Title of host publication	Sage Research Methods Cases
Publisher	Sage publications
Pages	–
DOIs	https://doi.org/10.4135/9781526449498
Publication status	Published - 2018
MoE publication type	D2 Article in professional manuals or guides or professional information systems or text book material

Access to Document

10.4135/9781526449498

https://methods.sagepub.com/case/associations-between-anxiety-premature-ejaculation-longitudinal-data-sem

Cite this

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title = "Analyzing Associations Between Anxiety and Premature Ejaculation Using Longitudinal Data and Structural Equation Modeling",

abstract = "As part of my PhD research project, I was interested in what causes premature ejaculation. This case study presents analyses on possible causal associations between premature ejaculation and anxiety, as well as sexual distress and depression. The statistical method, structural equation modeling, is introduced and applied, as is the concept of latent variables. The results showed no long-term associations between the study variables, and possible interpretations of this result are presented. Pros and cons of using a previously collected data set are discussed.",

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