Corrigenda: Small Sample Power Functions for Nonparametric Tests of Location in the Double Exponential Family

1977 ◽  
Vol 72 (359) ◽  
pp. 703
Keyword(s):  
Exponential Family ◽  
Nonparametric Tests ◽  
Small Sample ◽  
Power Functions ◽  
Double Exponential

scholarly journals Tests of Independence for a $2 \times 2$ Contingency Table with Random Margins

2017 ◽  
Vol 6 (2) ◽  
pp. 106 ◽  
Author(s):  
Yuan Yu ◽  
Dhiman Bhadra ◽  
Balgobin Nandram
Keyword(s):  
Contingency Table ◽  
Bayes Factor ◽  
Small Sample ◽  
Ratio Test ◽  
Power Functions ◽  
Significance Level ◽  
Exact Test ◽  
Fisher's Exact Test ◽  
Cell Counts ◽  
Fisher’S Exact Test

Fisher's exact test is commonly used for testing the hypothesis of independence between the row and column variables in a $r \times c$ contingency table. It is a ``small-sample'' test since it is used when the sample size is not large enough for the Pearsonian chi-square test to be valid. Fisher's exact test conditions on both margins of a $2 \times 2$ table leading to a hypergeometric distribution of the cell counts under independence. Moreover, it is conservative in the sense that its actual significance level falls short of the nominal level. In this paper, we modify Fisher's exact test by lifting the restriction of fixed margins and allow the margins to be random. In doing so, we propose two new tests - a likelihood ratio test in a frequentist framework and a Bayes factor test in a Bayesian framework, both of which are based on a new multinomial distributional framework. We apply the three tests on data from the Worcester Heart Attack study and compare their power functions in assessing gender difference in the therapeutic management of patients with acute myocardial infarction (AMI).

Comparison of Virtual Reality Visualizations With Traditional Visualizations in Hotel Settings

2020 ◽  
pp. 109634802095706
Author(s):  
Lisa Slevitch ◽  
Tilanka Chandrasekera ◽  
Meghan Drew Sealy
Keyword(s):  
Virtual Reality ◽  
Undergraduate Students ◽  
Small Sample Size ◽  
Research Question ◽  
Nonparametric Tests ◽  
Small Sample ◽  
South Central ◽  
Significant Difference ◽  
Quasi Experimental ◽  
Time Periods

The objective of the current study was to investigate how virtual reality (VR) visualizations compare with traditional visualizations such as two-dimensional (2D) photos as a marketing tool for hotel websites. The specific research question was “How do VR visualizations compare with 2D photos in terms of (1) affective responses, (2) attitudinal/behavioral responses, and (3) cognitive load—that is, task efforts and experiences associated with technology?” A quasi-experimental study was conducted over two time periods with independent sample pools. A boutique hotel lobby and a guest room were captured in 2D and VR formats. Subjects were randomly assigned to one of the two types of visualizations. The sample comprised 84 university undergraduate students from the South-Central United States. Nonparametric tests were used to test the proposed hypotheses. There was a statistically significant difference between two visual conditions for several variables—that is, pleasure, satisfaction, word of mouth, and so on. However, those differences were not always consistent between the two time periods. Overall findings suggest that the use of VR visualizations as a promotional tool might not be more effective than traditional photos. Limitations of the study include using students as a proxy for the general population of travelers, small sample size, self-reported measures, and narrow conditional scope. Those limitations should be addressed in future studies.

A new multivariate generalized log-double exponential family of distribution of kind-2

2018 ◽  
Vol 21 (1) ◽  
pp. 15-45
Author(s):  
G. S. David Sam Jayakumar ◽  
A. Solairaju ◽  
A. Sulthan
Keyword(s):  
Exponential Family ◽  
Double Exponential

Small-Sample Behavior of Some Multisample Nonparametric Tests for Scale

1975 ◽  
Vol 70 (352) ◽  
pp. 791-796 ◽  
Author(s):  
W. S. Tsai ◽  
B. S. Duran ◽  
T. O. Lewis
Keyword(s):  
Nonparametric Tests ◽  
Small Sample

Approximate Small-Sample Distributions for Multivariate Two-Sample Nonparametric Tests

Biometrics ◽  
1971 ◽  
Vol 27 (3) ◽  
pp. 515 ◽  
Author(s):  
Ralph A. Bradley ◽  
Kantilal M. Patel ◽  
Dennis D. Wackerly
Keyword(s):  
Nonparametric Tests ◽  
Small Sample
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