Randomization Test: An Alternative Analysis for the Difference of Two Means

Nuzzo, Regina

doi:10.1016/j.pmrj.2017.02.001

Cited by 24 publications

(22 citation statements)

References 11 publications

(12 reference statements)

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“…By “powerful,” we refer here to statistical power, which is the probability of rejecting the null hypothesis when it is, in fact, false (see Kyonka, in press, for discussion and a very helpful tutorial on statistical power with small‐ n samples). Simulation studies have demonstrated that randomization tests are often more powerful than other nonparametric tests and, in some cases, may be even more powerful than parametric statistics (see Ludbrook & Dudley, ; Nuzzo, ).…”

Section: Advantages Of Randomizationmentioning

confidence: 99%

Randomization tests as alternative analysis methods for behavior‐analytic data

Craig

Fisher

2019

J Exper Analysis Behavior

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Randomization statistics offer alternatives to many of the statistical methods commonly used in behavior analysis and the psychological sciences, more generally. These methods are more flexible than conventional parametric and nonparametric statistical techniques in that they make no assumptions about the underlying distribution of outcome variables, are relatively robust when applied to small‐n data sets, and are generally applicable to between‐groups, within‐subjects, mixed, and single‐case research designs. In the present article, we first will provide a historical overview of randomization methods. Next, we will discuss the properties of randomization statistics that may make them particularly well suited for analysis of behavior‐analytic data. We will introduce readers to the major assumptions that undergird randomization methods, as well as some practical and computational considerations for their application. Finally, we will demonstrate how randomization statistics may be calculated for mixed and single‐case research designs. Throughout, we will direct readers toward resources that they may find useful in developing randomization tests for their own data.

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Section: Advantages Of Randomizationmentioning

confidence: 99%

Randomization tests as alternative analysis methods for behavior‐analytic data

Craig

Fisher

2019

J Exper Analysis Behavior

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“…3 A, top row; supplementary movie S2), corresponding to an irradiance of 18.4 mW/cm 2 , polyps had expanded by 84% within 90 minutes (median value; 95% median confidence interval 0.75 -0.90). Within the same timeframe, but at 90 µW excitation power (82.6 mW/cm 2 irradiance), expansion was less than half (41%; 95% confidence interval 0.14 -0.64; p = 0.012 using randomisation test (Hooton, 1991;Nuzzo, 2017) (Fig. 3 A, bottom row; supplementary movie S3)).…”

Section: The Rate Of Polyp Expansion Depends On Excitation Light Irramentioning

confidence: 88%

Light-induced polyp retraction and tissue rupture in the photosensitive, reef-building coral Acropora muricata

Laissue

Qian

et al. 2019

Preprint

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Coral reefs are in alarming decline due to climate emergency, pollution and other man-made disturbances. The numerous ecosystem services derived from coral reefs are underpinned by the growth and physical complexity of reef-forming corals. Our knowledge of their fundamental biology is limited by available technology. We need a better understanding of larval settlement and development, skeletogenesis, interactions with pathogens and symbionts, and how this biology interacts with environmental factors such as light exposure, temperature, and ocean acidification. We here focus on a fast-growing key coloniser, Acropora muricata. To enable dynamic imaging of the photosensitive organism at different scales, we developed light-sheet illumination for fluorescence microscopy of small coral colonies. Our approach reveals live polyps in previously unseen detail. An imaging range for Acropora muricata with no measurable photodamage is defined based upon polyp expansion, coral tissue reaction, and photobleaching. We quantify polyp retraction as a photosensitive behavioural response and show sparse zooxanthellar expulsion and coral tissue rupture at higher intensities of blue light. The simple and flexible technique enables non-invasive continuous dynamic imaging of highly photosensitive organisms with sizes between 1 mm 3 and 5 cm 3 , for eight hours, at high temporal resolution, on a scale from multiple polyps down to cellular resolution. This live imaging tool opens a new window into the dynamics of reef-building corals. KEYWORDSLive imaging; coral development; phototoxicity; widefield fluorescence microscopy; confocal laser scanning microscopy; selective plane illumination microscopy; large selective plane illuminator.

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“…Another alternative for hypothesis testing when the samples to be compared are not normally distributed is to use rank‐based nonparametric tests, such as the Mann‐Whitney U test (Manly ). Most of the time, these tests have less power to correctly assess statistical significance than randomization tests because of the loss of information when converting data values into a ranking (Chen and Dunlap ; Nuzzo ). This power reduction is even more acute when there are several ties in the ranking (Chen and Dunlap ).…”

Section: Discussionmentioning

confidence: 99%

A method to test the significance of differences between centrographic measures of dispersion

López‐Castro

Thériault

Vandersmissen³

2018

Canadian Geographies / Géographies canadiennes

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Centrographic measures of spatial dispersion, such as the standard distance, provide a numerical value to summarize the radial scattering of a set of points around their centre of gravity or centroid. This paper develops a procedure to test for the statistical significance of differences in dispersion between two sets of phenomena intertwined in space. The significance test is implemented using a resampling randomization procedure based on the pooled locations from both sets to estimate the sampling distribution of their differences. Repeated thousands of times, that yields empirical frequency thresholds of the sampling distributions to assess the statistical significance of the observed differences. Case studies based on residential locations of lone‐parent families and retired couples in the Quebec City Metropolitan Area illustrate the procedure. This paper shows how randomization procedures can be used to adapt classical tests to assess the statistical significance of differences between indices of spatial dispersion.

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Randomization Test: An Alternative Analysis for the Difference of Two Means

Cited by 24 publications

References 11 publications

Randomization tests as alternative analysis methods for behavior‐analytic data

Randomization tests as alternative analysis methods for behavior‐analytic data

Light-induced polyp retraction and tissue rupture in the photosensitive, reef-building coral Acropora muricata

A method to test the significance of differences between centrographic measures of dispersion

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