Faking Detection Improved: Adopting a Likert Item Response Process Tree Model

2021 ◽  
pp. 109442812110029
Author(s):  
Tianjun Sun ◽  
Bo Zhang ◽  
Mengyang Cao ◽  
Fritz Drasgow
Keyword(s):  
Item Response ◽  
Personality Assessment ◽  
Personnel Selection ◽  
Process Model ◽  
Tree Model ◽  
High Stakes ◽  
New Approach ◽  
Job Applicant ◽  
Favorable Impression ◽  
Tree Modeling

With the increasing popularity of noncognitive inventories in personnel selection, organizations typically wish to be able to tell when a job applicant purposefully manufactures a favorable impression. Past faking research has primarily focused on how to reduce faking via instrument design, warnings, and statistical corrections for faking. This article took a new approach by examining the effects of faking (experimentally manipulated and contextually driven) on response processes. We modified a recently introduced item response theory tree modeling procedure, the three-process model, to identify faking in two studies. Study 1 examined self-reported vocational interest assessment responses using an induced faking experimental design. Study 2 examined self-reported personality assessment responses when some people were in a high-stakes situation (i.e., selection). Across the two studies, individuals instructed or expected to fake were found to engage in more extreme responding. By identifying the underlying differences between fakers and honest respondents, the new approach improves our understanding of faking. Percentage cutoffs based on extreme responding produced a faker classification precision of 85% on average.

scholarly journals Polarized Classification Tree Models: Theory and Computational Aspects

2021 ◽  
Author(s):  
Elena Ballante ◽  
Marta Galvani ◽  
Pierpaolo Uberti ◽  
Silvia Figini
Keyword(s):  
Information Gain ◽  
Classification Tree ◽  
Real Data ◽  
Simulation Framework ◽  
Tree Model ◽  
New Approach ◽  
Classification Tree Model ◽  
Tree Modeling ◽  
Tree Models ◽  
Computational Aspects

AbstractIn this paper, a new approach in classification models, called Polarized Classification Tree model, is introduced. From a methodological perspective, a new index of polarization to measure the goodness of splits in the growth of a classification tree is proposed. The new introduced measure tackles weaknesses of the classical ones used in classification trees (Gini and Information Gain), because it does not only measure the impurity but it also reflects the distribution of each covariate in the node, i.e., employing more discriminating covariates to split the data at each node. From a computational prospective, a new algorithm is proposed and implemented employing the new proposed measure in the growth of a tree. In order to show how our proposal works, a simulation exercise has been carried out. The results obtained in the simulation framework suggest that our proposal significantly outperforms impurity measures commonly adopted in classification tree modeling. Moreover, the empirical evidence on real data shows that Polarized Classification Tree models are competitive and sometimes better with respect to classical classification tree models.

Applying Item Response Trees to Personality Data in the Selection Context

2018 ◽  
Vol 22 (4) ◽  
pp. 1007-1018 ◽  
Author(s):  
David Michael LaHuis ◽  
Caitlin E. Blackmore ◽  
Kinsey Blue Bryant-Lees ◽  
Kristin Delgado
Keyword(s):  
Item Response ◽  
Personnel Selection ◽  
Decision Process ◽  
Latent Variables ◽  
Latent Variable ◽  
Decision Processes ◽  
Self Report ◽  
Tree Model ◽  
Tree Models ◽  
Better Than

Self-report personality scales are used frequently in personnel selection. Traditionally, researchers have assumed that individuals respond to items within these scales using a single-decision process. More recently, a flexible set of item response (IR) tree models have been developed that allow researchers to investigate multiple-decision processes. In the present research, we found that IR tree models fit the data better than a single-decision IR model when fitted to seven self-report personality scales used in a concurrent criterion-related validity study. In addition, we found evidence that the latent variable underlying the direction of a response (agree or disagree) decision process predicted job performance better than latent variables reflecting the other decision processes for the best fitting IR tree model.

Handwriting Analysis and Personality Assessment

2000 ◽  
Vol 5 (1) ◽  
pp. 44-51 ◽  
Author(s):  
Peter Greasley
Keyword(s):  
Personality Traits ◽  
Personality Assessment ◽  
Personnel Selection ◽  
Empirical Studies ◽  
Handwriting Analysis ◽  
Recruitment Process ◽  
Academic Literature ◽  
Personnel Recruitment ◽  
The Subject ◽  
Better Than

It has been estimated that graphology is used by over 80% of European companies as part of their personnel recruitment process. And yet, after over three decades of research into the validity of graphology as a means of assessing personality, we are left with a legacy of equivocal results. For every experiment that has provided evidence to show that graphologists are able to identify personality traits from features of handwriting, there are just as many to show that, under rigorously controlled conditions, graphologists perform no better than chance expectations. In light of this confusion, this paper takes a different approach to the subject by focusing on the rationale and modus operandi of graphology. When we take a closer look at the academic literature, we note that there is no discussion of the actual rules by which graphologists make their assessments of personality from handwriting samples. Examination of these rules reveals a practice founded upon analogy, symbolism, and metaphor in the absence of empirical studies that have established the associations between particular features of handwriting and personality traits proposed by graphologists. These rules guide both popular graphology and that practiced by professional graphologists in personnel selection.

Effects of Targeted Self-Coaching on Applicant Distortion of Personality Measures

2012 ◽  
Vol 11 (4) ◽  
pp. 169-175 ◽  
Author(s):  
Katherine A. Sliter ◽  
Neil D. Christiansen
Keyword(s):  
Impression Management ◽  
Personality Assessment ◽  
Personnel Selection ◽  
Lie Detection ◽  
Personality Test ◽  
Personality Measures ◽  
Personality Tests ◽  
The Impact

The present study evaluated the impact of reading self-coaching book excerpts on success at faking a personality test. Participants (N = 207) completed an initial honest personality assessment and a subsequent assessment with faking instructions under one of the following self-coaching conditions: no coaching, chapters from a commercial book on how to fake preemployment personality scales, and personality coaching plus a chapter on avoiding lie-detection scales. Results showed that those receiving coaching materials had greater success in raising their personality scores, primarily on the traits that had been targeted in the chapters. In addition, those who read the chapter on avoiding lie-detection scales scored significantly lower on a popular impression management scale while simultaneously increasing their personality scores. Implications for the use of personality tests in personnel selection are discussed.

Test-Taking Motivation and Personality Test Validity

2010 ◽  
Vol 9 (3) ◽  
pp. 117-125 ◽  
Author(s):  
Thomas A. O’Neill ◽  
Richard D. Goffin ◽  
Ian R. Gellatly
Keyword(s):  
Personality Assessment ◽  
Personnel Selection ◽  
Test Validity ◽  
Personality Testing ◽  
Personality Test ◽  
Field Sample ◽  
Moderation Effect ◽  
Test Taking ◽  
Low Levels ◽  
Valid Criterion

In this study we assessed whether the predictive validity of personality scores is stronger when respondent test-taking motivation (TTM) is higher rather than lower. Results from a field sample comprising 269 employees provided evidence for this moderation effect for one trait, Steadfastness. However, for Conscientiousness, valid criterion prediction was only obtained at low levels of TTM. Thus, it appears that TTM relates to the criterion validity of personality testing differently depending on the personality trait assessed. Overall, these and additional findings regarding the nomological net of TTM suggest that it is a unique construct that may have significant implications when personality assessment is used in personnel selection.

scholarly journals Investigation of Rater Effects Using Social Network Analysis and Exponential Random Graph Models

2017 ◽  
Vol 78 (3) ◽  
pp. 430-459 ◽  
Author(s):  
Iasonas Lamprianou
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Exponential Random Graph Models ◽  
Graph Models ◽  
High Stakes ◽  
Rating Data ◽  
New Approach ◽  
Exponential Random Graph ◽  
Rater Severity

It is common practice for assessment programs to organize qualifying sessions during which the raters (often known as “markers” or “judges”) demonstrate their consistency before operational rating commences. Because of the high-stakes nature of many rating activities, the research community tends to continuously explore new methods to analyze rating data. We used simulated and empirical data from two high-stakes language assessments, to propose a new approach, based on social network analysis and exponential graph models, to evaluate the readiness of a group of raters for operational rating. The results of this innovative approach are compared with the results of a Rasch analysis, which is a well-established approach for the analysis of such data. We also demonstrate how the new approach can be practically used to investigate important research questions such as whether rater severity is stable across rating tasks. The merits of the new approach, and the consequences for practice are discussed.

Expressed Symptoms and Personality Traits in Conversion Hysteria

1968 ◽  
Vol 23 (1) ◽  
pp. 231-243 ◽  
Author(s):  
Helen Schucman ◽  
William N. Thetford
Keyword(s):  
Personality Traits ◽  
Test Performance ◽  
Personality Assessment ◽  
Assessment System ◽  
New Approach ◽  
Personality Patterns ◽  
Personality Features

The study was based on the Personality Assessment System (PAS), a new approach to relating personality traits to Wechsler test performance. The purpose was to study relations between PAS personality patterns and expressed symptoms in conversion hysterics. This group was chosen because their symptoms presumably reflect essential personality features. The sample of 124 Ss was divided in 2 parts, the data being obtained and analyzed separately. 3 specific hypotheses, in line with PAS constructs, were formulated on the basis of findings obtained with the first part and tested with the second. 2 of the 3 hypotheses were upheld.

scholarly journals Recombination hotspots as a point process

2005 ◽  
Vol 360 (1460) ◽  
pp. 1597-1603 ◽  
Author(s):  
Maria De Iorio ◽  
Eric de Silva ◽  
Michael P.H Stumpf
Keyword(s):  
Point Process ◽  
Dna Sequences ◽  
Recombination Rate ◽  
Population Genetic ◽  
Process Model ◽  
Chromosomal Dna ◽  
New Approach ◽  
Recombination Hotspots ◽  
Minimum Number ◽  
Fully Bayesian

The variation of the recombination rate along chromosomal DNA is one of the important determinants of the patterns of linkage disequilibrium. A number of inferential methods have been developed which estimate the recombination rate and its variation from population genetic data. The majority of these methods are based on modelling the genealogical process underlying a sample of DNA sequences and thus explicitly include a model of the demographic process. Here we propose a different inferential procedure based on a previously introduced framework where recombination is modelled as a point process along a DNA sequence. The approach infers regions containing putative hotspots based on the inferred minimum number of recombination events; it thus depends only indirectly on the underlying population demography. A Poisson point process model with local rates is then used to infer patterns of recombination rate estimation in a fully Bayesian framework. We illustrate this new approach by applying it to several population genetic datasets, including a region with an experimentally confirmed recombination hotspot.

Reconciling the Theoretical and Empirical Study of International Norms: A New Approach to Measurement

2020 ◽  
pp. 1-8
Author(s):  
TYLER GIRARD
Keyword(s):  
Item Response ◽  
Bayesian Model ◽  
International Norms ◽  
Theoretical Understanding ◽  
New Approach ◽  
And Bisexual ◽  
National Analysis ◽  
Study Designs ◽  
Cross National

Abstract Despite extensive research on international norms, our approach to measurement has not kept pace with theoretical advancements. Existing research often relies on single indicators to facilitate cross-national analysis or employs case-study designs that provide greater nuance but restricted scope. Given these limitations, this note argues that item-response theory (IRT) provides a framework for strengthening the link between our theoretical understanding of norms and empirical measurement of norm adoption. In turn, I develop a modified Bayesian model with substantively informed dynamic priors. The proposed approach is evaluated with the lesbian, gay, and bisexual (LGB) equality norm, using 13 policies and laws across 196 countries (1990–2017). The results are broadly consistent with theoretical expectations while also providing new empirical evidence on the evolution of the norm across space and time. This note highlights the significant potential in greater interaction between both latent measurement approaches and scholarship on international norms.

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