One-Sample & Paired Samples t-tests: A Model Comparison Approach

2016 ◽  
Keyword(s):  
Model Comparison ◽  
Paired Samples ◽  
Comparison Approach

scholarly journals A Bayesian model comparison approach to test the specificity of visual integration impairment in schizophrenia or psychosis

2018 ◽  
Vol 265 ◽  
pp. 271-278 ◽  
Author(s):  
Tyler B. Grove ◽  
Beier Yao ◽  
Savanna A. Mueller ◽  
Merranda McLaughlin ◽  
Vicki L. Ellingrod ◽  
...  
Keyword(s):  
Bayesian Model ◽  
Model Comparison ◽  
Visual Integration ◽  
Bayesian Model Comparison ◽  
Comparison Approach

scholarly journals Capturing Ordinal Theoretical Constraint in Psychological Science

2018 ◽  
Author(s):  
Julia M. Haaf ◽  
Fayette Klaassen ◽  
Jeffrey Rouder
Keyword(s):  
Social Sciences ◽  
Linear Model ◽  
Bayesian Model ◽  
Model Comparison ◽  
Social Scientists ◽  
Psychological Science ◽  
Bayesian Model Comparison ◽  
Comparison Approach ◽  
The Social ◽  
Ordinal Level

Most theories in the social sciences are verbal and provide ordinal-level predictions for data. For example, a theory might predict that performance is better in one condition than another, but not by how much. One way of gaining additional specificity is to posit many ordinal constraints that hold simultaneously. For example a theory might predict an effect in one condition, a larger effect in another, and none in a third. We show how common theoretical positions naturally lead to multiple ordinal constraints. To assess whether multiple ordinal constraints hold in data, we adopt a Bayesian model comparison approach. The result is an inferential system that is custom-tuned for the way social scientists conceptualize theory, and that is more intuitive and informative than current linear-model approaches.

Assessing the relevance of fMRI-based prior in the EEG inverse problem: a bayesian model comparison approach

2005 ◽  
Vol 53 (9) ◽  
pp. 3461-3472 ◽  
Author(s):  
J. Daunizeau ◽  
C. Grova ◽  
J. Mattout ◽  
G. Marrelec ◽  
D. Clonda ◽  
...  
Keyword(s):  
Inverse Problem ◽  
Bayesian Model ◽  
Model Comparison ◽  
Bayesian Model Comparison ◽  
Comparison Approach ◽  
Eeg Inverse Problem

Data Analysis: A Model-Comparison Approach.

1990 ◽  
Vol 85 (410) ◽  
pp. 600
Author(s):  
Virginia Clark ◽  
Charles M. Judd ◽  
Gary H. McClelland
Keyword(s):  
Data Analysis ◽  
Model Comparison ◽  
Comparison Approach

scholarly journals The genomic formation of First American ancestors in East and Northeast Asia

2020 ◽  
Author(s):  
Chao Ning ◽  
Daniel Fernandes ◽  
Piya Changmai ◽  
Olga Flegontova ◽  
Eren Yüncü ◽  
...  
Keyword(s):  
Native Americans ◽  
River Basin ◽  
Model Comparison ◽  
Northeast Asia ◽  
Graph Model ◽  
Amur River Basin ◽  
Amur River ◽  
North Americans ◽  
Comparison Approach ◽  
First Americans

AbstractUpward Sun River 1, an individual from a unique burial of the Denali tradition in Alaska (11500 calBP), is considered a type representative of Ancient Beringians who split from other First Americans 22000–18000 calBP in Beringia. Using a new admixture graph model-comparison approach resistant to overfitting, we show that Ancient Beringians do not form the deepest American lineage, but instead harbor ancestry from a lineage more closely related to northern North Americans than to southern North Americans. Ancient Beringians also harbor substantial admixture from a lineage that did not contribute to other Native Americans: Amur River Basin populations represented by a newly reported site in northeastern China. Relying on these results, we propose a new model for the genomic formation of First American ancestors in Asia.One Sentence SummaryAncient Beringians do not form the deepest American lineage, but harbor admixture from Amur River Basin populations.

scholarly journals From theories to models to predictions: A Bayesian model comparison approach

2017 ◽  
Author(s):  
Jeffrey Rouder ◽  
Julia M. Haaf ◽  
Frederik Aust
Keyword(s):  
Statistical Models ◽  
Bayesian Model ◽  
Model Comparison ◽  
Bayes Factor ◽  
Significance Testing ◽  
Bayesian Model Comparison ◽  
Comparison Approach ◽  
Competing Models ◽  
Competing Hypotheses

A key goal in research is to use data to assess competing hypotheses or theories. Analternative to the conventional significance testing is Bayesian model comparison. The mainidea is that competing theories are represented by statistical models. In the Bayesianframework, these models then yield predictions about data even before the data are seen.How well the data match the predictions under competing models may be calculated, andthe ratio of these matches—the Bayes factor—is used to assess the evidence for one modelcompared to another. We illustrate the process of going from theories to models and topredictions in the context of two hypothetical examples about how exposure to media affectsattitudes toward refugees.

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