Quantifying idiosyncratic and shared contributions to stimulus evaluations

2018 ◽  
Author(s):  
Joel Eduardo Martinez ◽  
Friederike Funk ◽  
Alexander Todorov
Keyword(s):  
Repeated Measures ◽  
Variance Component ◽  
Psychological Problem ◽  
Psychological Research ◽  
Large Variability ◽  
Four Dimensions ◽  
Stimulus Evaluation ◽  
Crossed Random Effects ◽  
Novel Objects ◽  
Variance Component Estimates

A fundamental psychological problem is identifying the idiosyncratic and shared contributions to stimulus evaluation. However, there is no established method for estimating these contributions and the existing methods have led to divergent estimates. Moreover, in many studies participants rate the stimuli only once, although at least two measurements are required to estimate idiosyncratic contributions. Here, participants rated faces or novel objects on four dimensions (beautiful, approachable, likeable, dangerous) for a total of ten blocks to better estimate the preferences of individual raters. First, we show that both intra-rater and inter-rater agreement – measures related to idiosyncratic and shared contributions, respectively – increase with repeated measures. Second, to find best practices, we compared estimates from correlation indices and variance component approaches on stimulus-generality, evaluation-generality, data preprocessing steps, and sensitivity to measurement error (a largely ignored issue). The correlation indices changed monotonically and nonlinearly with more repeated measures. Variance component analyses showed large variability in estimates from only two repeated measures, but stabilized with more measures. While there was general agreement among approaches, the correlation approach was problematic for certain stimulus types and evaluation dimensions. Our results suggest that variance component estimates are more reliable as long as one collects more than two repeated measures, which is not the current norm in psychological research, and can be implemented using mixed models with crossed random effects. Recommendations for analysis and interpretations are provided.

Quantifying idiosyncratic and shared contributions to judgment

2018 ◽  
Author(s):  
Joel Eduardo Martinez ◽  
Friederike Funk ◽  
Alexander Todorov
Keyword(s):  
Mixed Models ◽  
Repeated Measures ◽  
Variance Component ◽  
Rater Agreement ◽  
Established Method ◽  
Rater Reliability ◽  
Set Size ◽  
Crossed Random Effects ◽  
Precision Study ◽  
Estimate Precision

Identifying relative idiosyncratic and shared contributions to judgments is a fundamental challenge to the study of human behavior, yet there is no established method for estimating these contributions. Using edge cases of stimuli varying in intra-rater reliability and inter-rater agreement – faces (high on both), objects (high on the former, low on the latter), and complex patterns (low on both) – we show that variance component analyses (VCAs) accurately captured the psychometric properties of the data (Study 1). Simulations showed the VCA generalizes to any arbitrary continuous rating and both sample and stimulus set size affect estimate precision (Study 2). Generally, a minimum of 60 raters and 30 stimuli provided reasonable estimates within our simulations. Furthermore, VCA estimates stabilized given more than two repeated measures, consistent with the finding that both intra-rater reliability and inter-rater agreement increased nonlinearly with repeated measures (Study 3). The VCA provides a rigorous examination of where variance lies in the data, can be implement using mixed models with crossed random effects, and is general enough to be useful in any judgment domain where agreement and disagreement are important to quantify and multiple raters independently rate multiple stimuli.

scholarly journals Variance component estimates for alternative litter size traits in swine

2015 ◽  
Vol 93 (11) ◽  
pp. 5153-5163 ◽  
Author(s):  
A. M. Putz ◽  
F. Tiezzi ◽  
C. Maltecca ◽  
K. A. Gray ◽  
M. T. Knauer
Keyword(s):  
Litter Size ◽  
Variance Component ◽  
Variance Component Estimates

Sire-by-herd interaction effect when variances across herds are heterogeneous. II. Within-herd variance-component estimates

1995 ◽  
Vol 112 (1-6) ◽  
pp. 107-116 ◽  
Author(s):  
F. Canavesi ◽  
L. R. Schaeffer ◽  
E. B. Burnside ◽  
G. B. Jansen ◽  
P. Rozzi
Keyword(s):  
Interaction Effect ◽  
Variance Component ◽  
Variance Component Estimates

scholarly journals Building Blocks for Alternative Four-Dimensional Pyramids of Corporate Social Responsibilities

2016 ◽  
Vol 58 (2) ◽  
pp. 404-438 ◽  
Author(s):  
Timo Meynhardt ◽  
Peter Gomez
Keyword(s):  
Corporate Citizenship ◽  
Building Blocks ◽  
Psychological Research ◽  
Four Dimensions ◽  
The Public ◽  
Human Needs ◽  
Alternative Approach ◽  
Dialogue Process ◽  
Economic Foundation ◽  
Corporate Social

Carroll shaped the corporate social responsibility (CSR) discourse into a four-dimensional pyramid framework, which was later adapted to corporate citizenship and sustainability approaches. The four layers of the pyramid—structured from foundation to apex as economic, legal, ethical, and philanthropic (or discretionary) responsibilities—drew considerable managerial attention. An important criticism of the economic foundation of the Carroll pyramid concerns the identification and ordering of the four dimensions, which are inadequately justified theoretically. The authors of this article propose an alternative approach that builds on the public value concept, which integrates a microfoundation of psychological research into basic human needs. Drawing on their Swiss Dialogue process, the authors argue that a four-dimensional pyramid does have heuristic value for managers. The advantage of this alternative pyramid logic is that it may be contingently adapted to different cultural contexts, because it allows adaptive internal reordering.

Visual Demerit and Microbiological Evaluation of Beef Carcasses: Methodology

1993 ◽  
Vol 56 (2) ◽  
pp. 114-119 ◽  
Author(s):  
KLAUS W. F. JERICHO ◽  
JOHN A. BRADLEY ◽  
VICTOR P. J. GANNON ◽  
GERALD C. KOZUB
Keyword(s):  
Variance Component ◽  
Most Probable Number ◽  
Inspection System ◽  
Bacterial Populations ◽  
Probable Number ◽  
Automated Method ◽  
Weak Association ◽  
Beef Carcasses ◽  
Good Repeatability ◽  
Variance Component Estimates

A repeatable, automated method was developed for estimating aerobic bacterial populations on surfaces of groups of beef carcasses. Ten sample cluster sites (CS) were identified by localizing visual demerits (Canadian Streamlined Inspection System) on 200 carcasses at one plant. Most probable number growth units per cm2 (MPNGU/cm2) on hydrophobic grid membrane filters (HGMF) were assessed by an automated HGMF interpreter for excision samples from the centers of these CS. Between-sample variation of more than 90% of the total log10 MPNGU/cm2 variance indicated good repeatability between HGMF of the same sample and interpretations of the same HGMF. Variance component estimates indicated that there was considerable variation in MPNGU/cm2 between carcasses and between paired adjacent samples for a CS. A statistically significant but weak association was found between the demerit scores of a CS and MPNGU at its center. The variance component estimates will be used to estimate the sample size required for future group-carcass evaluations.

scholarly journals How to deal with genotype uncertainty in variance component quantitative trait loci analyses

2011 ◽  
Vol 93 (5) ◽  
pp. 333-342 ◽  
Author(s):  
XIA SHEN ◽  
LARS RÖNNEGÅRD ◽  
ÖRJAN CARLBORG
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Complex Traits ◽  
Variance Component ◽  
Large Animal ◽  
Trait Loci ◽  
Sib Families ◽  
Variance Component Estimates ◽  
Variance Component Models ◽  
Component Models

SummaryDealing with genotype uncertainty is an ongoing issue in genetic analyses of complex traits. Here we consider genotype uncertainty in quantitative trait loci (QTL) analyses for large crosses in variance component models, where the genetic information is included in identity-by-descent (IBD) matrices. An IBD matrix is one realization from a distribution of potential IBD matrices given available marker information. In QTL analyses, its expectation is normally used resulting in potentially reduced accuracy and loss of power. Previously, IBD distributions have been included in models for small human full-sib families. We develop an Expectation–Maximization (EM) algorithm for estimating a full model based on Monte Carlo imputation for applications in large animal pedigrees. Our simulations show that the bias of variance component estimates using traditional expected IBD matrix can be adjusted by accounting for the distribution and that the calculations are computationally feasible for large pedigrees.

Estimates of genetic parameters for ultrasound-measured carcass traits in sheep

2004 ◽  
Vol 84 (3) ◽  
pp. 361-365 ◽  
Author(s):  
T. L. Fernandes ◽  
J. W. Wilton ◽  
J. J. Tosh
Keyword(s):  
Genetic Improvement ◽  
Variance Component ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Genetic Effect ◽  
Backfat Thickness ◽  
Additive Genetic Effect ◽  
Multiple Trait ◽  
Breed Group ◽  
Variance Component Estimates

Data on ultrasound traits (loin depth, average backfat thickness, and loin width) were collected from lambs (n = 3483) across Ontario, born between 1997 and 1999. The data were analysed with a REML procedure in a multiple-trait mixed-animal model to obtain (co)variance component estimates. Analyses of all traits included the additive genetic effect of the lamb, sex of the lamb, contemporary group, and breed group effects. Weight or age was included as a covariate in two separate analyses. Estimates of direct additive heritabilities for loin depth, average backfat thickness, and loin width were 0.29, 0.29 and 0.26 respectively, with genetic correlations of -0.17 between loin depth and average backfat thickness, 0.43 between loin depth and loin width, and 0.23 between loin width and average backfat thickness for the weight constant analysis. When the data were analysed using age in the regression analysis, corresponding estimates of direct additive heritabilities were 0.38, 0.35 and 0.30, and genetic correlations between traits were all positive, 0.29 between loin depth and average backfat thickness, 0.61 between loin depth and loin width, and 0.44 between loin width and average backfat thickness. Results indicate that it is possible to make genetic improvement if selection is based on ultrasound information. Key words: Sheep, genetic parameters, heritability, ultrasound

Sign in / Sign up

Export Citation Format

Share Document