Dyadic Data Analysis

Released on by David A. Kenny
preview-18

  • Dyadic Data Analysis Book Detail

  • Author : David A. Kenny
  • Release Date : 2020-11-26
  • Publisher : Guilford Publications
  • Genre : Psychology
  • Pages : 482
  • ISBN 13 : 1462546137
  • File Size : 94,94 MB
DOWNLOAD BOOK

Dyadic Data Analysis by David A. Kenny PDF Summary

Book Description: Interpersonal phenomena such as attachment, conflict, person perception, learning, and influence have traditionally been studied by examining individuals in isolation, which falls short of capturing their truly interpersonal nature. This book offers state-of-the-art solutions to this age-old problem by presenting methodological and data-analytic approaches useful in investigating processes that take place among dyads: couples, coworkers, parent and child, teacher and student, or doctor and patient, to name just a few. Rich examples from psychology and across the behavioral and social sciences help build the researcher's ability to conceptualize relationship processes; model and test for actor effects, partner effects, and relationship effects; and model and control for the statistical interdependence that can exist between partners. The companion website provides clarifications, elaborations, corrections, and data and files for each chapter.

Disclaimer: www.yourbookbest.com does not own Dyadic Data Analysis books pdf, neither created or scanned. We just provide the link that is already available on the internet, public domain and in Google Drive. If any way it violates the law or has any issues, then kindly mail us via contact us page to request the removal of the link.

Dyadic Data Analysis

Dyadic Data Analysis

File Size : 99,99 MB
Total View : 5216 Views
DOWNLOAD

Interpersonal phenomena such as attachment, conflict, person perception, learning, and influence have traditionally been studied by examining individuals in iso

Correlation and Causality

Correlation and Causality

File Size : 75,75 MB
Total View : 8807 Views
DOWNLOAD

Structural modeling; Covariance algebra; Principles of path analysis; Models with observed variables as causes; Measurement error in the exogenous variable and