Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
  1. Home
  2. Search

Refine search

Refine search

Access:
Content type:
Publication date:
Apply   From and To filters
Subject: Show more
Journals Show more
Publishers: Show more
Societies Show more
Series: Show more
Collections: Show more

Actions for selected content:

Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Save to Kindle
  • Save to Dropbox
  • Save to Google Drive

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
Cancel
×

4 results

  • 26 - Multilevel Modeling

  • from Part IV - Statistical Approaches
  • Edited by Austin Lee Nichols, Central European University, Vienna, John Edlund, Rochester Institute of Technology, New York
  • Book:
    The Cambridge Handbook of Research Methods and Statistics for the Social and Behavioral Sciences
    Published online:
    25 May 2023
    Print publication:
    08 June 2023, pp 559-582

  • Summary

    This chapter provides a brief introduction to multilevel models, specifically organizational models, and should be accessible to researchers who are familiar with ordinary least-squares (OLS) regression (i.e., multiple regression models). OLS regression assumes independence of observations; however, the responses of people clustered within organizational units (e.g., schools, classrooms, hospitals, companies) are likely to exhibit some degree of relatedness. In such scenarios, violating the assumption of independence produces incorrect standard errors that are smaller than they should be – multilevel modeling can alleviate this concern. However, the advantages of multilevel modeling are not purely statistical. Substantively, researchers may seek to understand the degree to which people from the same cluster are similar to each other and identify variables that predict variability within and across clusters. Multilevel analyses allow us to exploit the information in clustered samples and partition variance in the outcome variable into between-cluster and within-cluster variability. We can also use predictors at both the individual (level 1) and group (level 2) levels to explain this between- and within-cluster outcome variance.

  • The expression of positive and negative schizotypy in daily life: an experience sampling study

  • T. R. Kwapil, L. H. Brown, P. J. Silvia, I. Myin-Germeys, N. Barrantes-Vidal
  • Journal:
    Psychological Medicine / Volume 42 / Issue 12 / December 2012
    Published online by Cambridge University Press:
    27 April 2012, pp. 2555-2566
  • Background

    Psychometrically identified positive schizotypy and negative schizotypy are differentially related to psychopathology, personality and social functioning. However, little is known about the experience and expression of schizotypy in daily life and the psychological mechanisms that trigger psychotic-like experiences.

    Method

    The present study employed experience sampling methodology (ESM) to assess positive and negative schizotypy in daily life in a non-clinical sample of 412 young adults. ESM is a structured diary technique in which participants are prompted at random times during the day to complete assessments of their current experiences.

    Results

    As hypothesized, positive schizotypy was associated with increased negative affect, thought impairment, suspiciousness, negative beliefs about current activities and feelings of rejection, but not with social disinterest or decreased positive affect. Negative schizotypy, on the other hand, was associated with decreased positive affect and pleasure in daily life, increased negative affect, and decreases in social contact and interest. Both positive schizotypy and negative schizotypy were associated with the desire to be alone when with others. However, this was moderated by anxiety in positive schizotypy and by diminished positive affect in negative schizotypy.

    Conclusions

    The results support the construct validity of a multidimensional model of schizotypy and the ecological validity of the positive and negative schizotypy dimensions. ESM appears to be a promising method for examining the daily life experiences of schizotypic individuals.

  • Cardiovascular patterns associated with threat and challenge appraisals: A within-subjects analysis

  • KAREN S. QUIGLEY, LISA FELDMAN BARRETT, SUZANNE WEINSTEIN
  • Journal:
    Psychophysiology / Volume 39 / Issue 3 / May 2002
    Published online by Cambridge University Press:
    15 May 2002, pp. 292-302
    Print publication:
    May 2002

  • Previous studies demonstrated distinct cardiovascular patterns associated with threat and challenge appraisals for groups of participants. We extend these results by assessing whether appraisals continue to be associated with these cardiovascular response patterns within an individual as appraisals change. Participants completed four verbal mental arithmetic tasks for which they made appraisals before and after each task. Cardiac reactivity and total peripheral resistance (TPR) were calculated for the first and last minutes of each task, and the number of responses and percent correct were measured for each task. In line with our prediction, pretask appraisals were related to some task-related cardiac responses across the four tasks. In addition, task-related cardiovascular reactivity and behaviors both influenced appraisals following the task. Our findings suggest that an idiographic analysis of appraisals, cardiovascular physiology, and task-related behaviors provides a richer understanding of the appraisal process and reveals sex differences deserving further assessment.