Open Access. Powered by Scholars. Published by Universities.®

Statistical Models Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 9 of 9

Full-Text Articles in Statistical Models

How Sexism Makes The Man: Examining The Relationship Between Masculinity, Ambivalent Sexism, And Gender Stereotyping, Mariah L. Wilkerson Jun 2014

How Sexism Makes The Man: Examining The Relationship Between Masculinity, Ambivalent Sexism, And Gender Stereotyping, Mariah L. Wilkerson

Lawrence University Honors Projects

Masculinity is a precarious social status, meaning it can be lost through social and gender transgressions (Bosson & Vandello, 2011). Men often act in stereotypically masculine ways to reassert their masculinity and restore their social status after it has been threatened. The current study also examines masculinity in a new way, as a collective gender identity (e.g., Tajfel, 1982). I hypothesized that threatened men and men who identify as more masculine will display masculinity through more polarized attitudes towards traditional and nontraditional groups of men and women, endorsing traditional gender stereotypes, and intensified ambivalently sexist attitudes. Two empirical studies tested …


Hierarchical Graphical Bayesian Models In Psychology, Guillermo Campitelli, Guillermo Macbeth Jan 2014

Hierarchical Graphical Bayesian Models In Psychology, Guillermo Campitelli, Guillermo Macbeth

Research outputs 2014 to 2021

The improvement of graphical methods in psychological research can promote their use and a better comprehension of their expressive power. The application of hierarchical Bayesian graphical models has recently become more frequent in psychological research. The aim of this contribution is to introduce suggestions for the improvement of hierarchical Bayesian graphical models in psychology. This novel set of suggestions stems from the description and comparison between two main approaches concerned with the use of plate notation and distribution pictograms. It is concluded that the combination of relevant aspects of both models might improve the use of powerful hierarchical Bayesian graphical …


Configuration As A Source Of Information, Joseph W. Houpt, Robert D. Hawkins, Ami Eidels, James T. Townsend, Michael J. Wenger Nov 2011

Configuration As A Source Of Information, Joseph W. Houpt, Robert D. Hawkins, Ami Eidels, James T. Townsend, Michael J. Wenger

Psychology Faculty Publications

No abstract provided.


Fundamental Properties Of Simple Emergent Feature Processing, Robert D. Hawkins, Joseph W. Houpt, Ami Eidels, James T. Townsend, Michael J. Wenger Nov 2011

Fundamental Properties Of Simple Emergent Feature Processing, Robert D. Hawkins, Joseph W. Houpt, Ami Eidels, James T. Townsend, Michael J. Wenger

Psychology Faculty Publications

No abstract provided.


A Statistical Test For The Capacity Coefficient, Joseph W. Houpt, James T. Townsend Jul 2011

A Statistical Test For The Capacity Coefficient, Joseph W. Houpt, James T. Townsend

Psychology Faculty Publications

No abstract provided.


From Deep Space 9 To The Gamma Quadrant!, James T. Townsend, Joseph W. Houpt Jul 2011

From Deep Space 9 To The Gamma Quadrant!, James T. Townsend, Joseph W. Houpt

Psychology Faculty Publications

No abstract provided.


An Extension Of Sic Predictions To The Wiener Coactive Model, Joseph W. Houpt, James T. Townsend Jun 2011

An Extension Of Sic Predictions To The Wiener Coactive Model, Joseph W. Houpt, James T. Townsend

Psychology Faculty Publications

The survivor interaction contrasts (SIC) is a powerful measure for distinguishing among candidate models of human information processing. One class of models to which SIC analysis can apply are the coactive, or channel summation, models of human information processing. In general, parametric forms of coactive models assume that responses are made based on the first passage time across a fixed threshold of a sum of stochastic processes. Previous work has shown that the SIC for a coactive model based on the sum of Poisson processes has a distinctive down--up--down form, with an early negative region that is smaller than the …


Nice Guys Finish Fast And Bad Guys Finish Last: Facilitatory Vs. Inhibitory Interaction In Parallel Systems, Ami Eidels, Joseph W. Houpt, Nicholas Altieri, Lei Pei, James T. Townsend Apr 2011

Nice Guys Finish Fast And Bad Guys Finish Last: Facilitatory Vs. Inhibitory Interaction In Parallel Systems, Ami Eidels, Joseph W. Houpt, Nicholas Altieri, Lei Pei, James T. Townsend

Psychology Faculty Publications

Systems Factorial Technology is a powerful framework for investigating the fundamental properties of human information processing such as architecture (i.e., serial or parallel processing) and capacity (how processing efficiency is affected by increased workload). The Survivor Interaction Contrast (SIC) and the Capacity Coefficient are effective measures in determining these underlying properties, based on response-time data. Each of the different architectures, under the assumption of independent processing, predicts a specific form of the SIC along with some range of capacity. In this study, we explored SIC predictions of discrete-state (Markov process) and continuous-state (Linear Dynamic) models that allow for certain types …


The Statistical Properties Of The Survivor Interaction Contrast, Joseph W. Houpt, James T. Townsend Oct 2010

The Statistical Properties Of The Survivor Interaction Contrast, Joseph W. Houpt, James T. Townsend

Psychology Faculty Publications

The Survivor Interaction Contrast (SIC) is a powerful tool for assessing the architecture and stopping rule of a model of mental processes. Despite its demonstrated utility, the methodology has lacked a method for statistical testing until now. In this paper we briefly describe the SIC then develop some basic statistical properties of the measure. These developments lead to a statistical test for rejecting certain classes of models based on the SIC. We verify these tests using simulated data, then demonstrate their use on data from a simple cognitive task.