Minimum Detectable Effect Size Computations for Cluster-Level Regression Discontinuity Studies: Specifications Beyond the Linear Functional Form

The present study was undertaken to study the trends of area, production and productivity of pineapple in Manipur. The study was based on the secondary data from 2001 to 2011. To analyze the trend of area, production and productivity of pineapple in Manipur, semi log linear functional form was used. Beside these, compound growth rate and instability index was also estimated. The effect of area, production and their interaction towards increasing production were also estimated in the present study. The instability indices for area, production and productivity of pineapple crop in Manipur were positive there by indicating less risk for growing pineapple in the State.

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On the Functional Form of the Transition Probabilities in the Monte Carlo Method as Used in Statistical Mechanics

Australian Journal of Physics ◽

10.1071/ph790455 ◽

1979 ◽

Vol 32 (5) ◽

pp. 455

Author(s):

CHJ Johnson

Keyword(s):

Monte Carlo ◽

Statistical Mechanics ◽

Linear Functional ◽

Functional Form ◽

Transition Probabilities ◽

Mean Field ◽

Linear Functional Equation ◽

Analytical Comparison ◽

Simulation Process ◽

The Monte Carlo Method

The transition probabilities W in the traditional Monte Carlo simulation process used in statistical mechanics are shown to satisfy a linear functional equation. General classes of solution to this equation are presented. A simple one-particle mean-field Ising model of a ferromagnet is used in an analytical comparison of the various possible forms of W.

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Small effect-size mutations cumulatively affect yeast quantitative traits

10.1101/126409 ◽

2017 ◽

Cited By ~ 1

Author(s):

Bo Hua ◽

Michael Springer

Keyword(s):

Effect Size ◽

Quantitative Trait ◽

Quantitative Traits ◽

Detectable Effect ◽

List Type ◽

Trait Variation ◽

Cellular Processes ◽

Small Effect Size ◽

Pathway Function

SummaryQuantitative traits are influenced by pathways that have traditionally been defined through genes that have a large loss- or gain-of-function effect. However, in theory, a large number of small effect-size genes could cumulative play a substantial role in pathway function, potentially by acting as “modifiers” that tune the levels of large effect size pathway components. To understand the role of these small effect-size genes, we used a quantitative assay to determine the number, strength, and identity of all non-essential genes that affect two galactose-responsive (GAL) traits, in addition to re-analyzing two previously screened quantitative traits. Over a quarter of assayed genes have a detectable effect; approximately two thirds of the quantitative trait variation comes from small effect-size genes. The functions of small effect-size genes are partially overlapping between traits and are enriched in core cellular processes. This implies that genetic variation in one process has the potential to influence behavior or disease in seemingly unconnected processes.HighlightsFour yeast quantitative traits are affected by thousands of small effect-size genes.Small effect-size genes are enriched in core cellular processesThe effects of these genes are quantitative trait-specific.

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Clinical differences between children with asthma and rhinitis in rural and urban areas

Colombia Medica ◽

10.25100/cm.v50i1.4196 ◽

2019 ◽

pp. 46-48

Author(s):

Andrés Fandiño Losada

Keyword(s):

Sample Size ◽

Effect Size ◽

Rural Areas ◽

Urban Areas ◽

Sample Size Calculation ◽

Detectable Effect ◽

Asthma Control Test ◽

Cross Sectional ◽

Interesting Study ◽

The Difference

Dear Editors: In their article, Sánchez, et al 1 have reported about an interesting study on asthma and rhinitis symptoms among children in urban and rural Colombian areas, describing that the control of symptoms, over time, is more difficult among children in urban areas. Their article has the methodological advantage of having done a prospective follow-up of pediatric patients with asthma and rhinitis; nevertheless I have some questions: 1) The sample size calculation is not clear. The authors mentioned the prevalence of asthma and rhinitis in the urban areas and their corresponding error, but they did not use these parameters in the sample size calculation. On the other hand, the authors argued that the main outcome was comparing the treatment of asthma and rhinitis between urban and rural areas; thus readers could assume that the measure of effect was the difference of the Asthma Control Test (ACT) score between both areas; but the authors did not clearly explain it. Furthermore, it is not clear why the ratio of urban/rural subjects is 1.57; is the ratio observed in the study health centers? In this line, it seems that the appropriate sample size calculation must have been the difference of means between two independent populations, although the authors did not report any ACT effect size based on previous studies. Thus, I have estimated the means difference (as the effect size) given the power (80%) and the study sample size (urban= 201 and rural= 128) provided by the authors; using Stata® 14.2 (power twomeans command). In this manner, the detectable effect size would be 3.5; which is higher than the ACT effect size estimated in the Sánchez, Sánchez and Cardona’s article (i.e.: 3.0), leading to an underpowered study, at least for the cross-sectional estimates. In this manner, what was the appropriate sample size calculation?

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Oxytocin-Trust Link in Oxytocin-Sensitive Participants and Those Without Autistic Traits

Frontiers in Neuroscience ◽

10.3389/fnins.2021.659737 ◽

2021 ◽

Vol 15 ◽

Author(s):

Hirofumi Kurokawa ◽

Yusuke Kinari ◽

Hiroko Okudaira ◽

Kiyotaka Tsubouchi ◽

Yoshimichi Sai ◽

...

Keyword(s):

Effect Size ◽

Autistic Traits ◽

Autism Spectrum ◽

Interindividual Variation ◽

Detectable Effect ◽

Autism Spectrum Quotient ◽

Double Blind ◽

Exact Test ◽

The Mean

There have been numerous studies in which the biological role of oxytocin in trusting behavior has been investigated. However, a link between oxytocin and trust in humans was discovered only in one early study. We hypothesized that there is a large interindividual variation in oxytocin sensitivity, and that such variation is one reason for the doubt surrounding the role of oxytocin in trusting behavior. Here, in a double-blind, prospective, case-control study, we administered intranasal oxytocin to participants of trust and risk games. We measured salivary oxytocin concentration, relating it to the amount of money transferred among participants (a proxy for trust) and the autism-spectrum quotient (AQ). A one-sided Fisher’s exact test was performed to detect differences between the oxytocin and placebo groups in the proportions of investors who transferred the maximum amount of money. We discovered a tendency for participants who received oxytocin to transfer higher amounts of money to co-participants than those who received a placebo (P = 0.04). We also revealed a high degree of interindividual variation in salivary oxytocin concentrations after oxytocin administration. After stratifying the samples with respect to oxytocin sensitivity, oxytocin-sensitive participants in the oxytocin group also transferred higher amounts of money than those in the placebo group (P = 0.03), while such a tendency was not observed for oxytocin-insensitive participants (P = 0.34). Participants with lower AQ scores (less severe autistic traits) exhibited a greater tendency toward trusting behavior after oxytocin administration than did those with higher AQ scores (P = 0.02). A two-sample t-test that was performed to detect significant differences in the mean transfers between the oxytocin and placebo groups indicated no significant between-group difference in the mean transfers (P = 0.08). There are two possible interpretations of these results: First, there is no effect of oxytocin on trust in humans; second, the effects of oxytocin on trust in humans is person-dependent. However, the results should be interpreted with caution as the effect size was not larger than the minimal detectable effect size and the results were not statistically significant (P > 0.05) after Bonferroni corrections.

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Comparative Regression Discontinuity: A Stress Test With Small Samples

Evaluation Review ◽

10.1177/0193841x18776881 ◽

2018 ◽

Vol 42 (1) ◽

pp. 111-143 ◽

Cited By ~ 3

Author(s):

Yasemin Kisbu-Sakarya ◽

Thomas D. Cook ◽

Yang Tang ◽

M. H. Clark

Keyword(s):

Statistical Power ◽

Functional Form ◽

Regression Discontinuity ◽

Stress Test ◽

Regression Line ◽

Small Samples ◽

Outcome Analysis ◽

Comparison Function ◽

Regression Discontinuity Design ◽

Entire Study

Compared to the randomized experiment (RE), the regression discontinuity design (RDD) has three main limitations: (1) In expectation, its results are unbiased only at the treatment cutoff and not for the entire study population; (2) it is less efficient than the RE and so requires more cases for the same statistical power; and (3) it requires correctly specifying the functional form that relates the assignment and outcome variables. One way to overcome these limitations might be to add a no-treatment functional form to the basic RDD and including it in the outcome analysis as a comparison function rather than as a covariate to increase power. Doing this creates a comparative regression discontinuity design (CRD). It has three untreated regression lines. Two are in the untreated segment of the RDD—the usual RDD one and the added untreated comparison function—while the third is in the treated RDD segment. Also observed is the treated regression line in the treated segment. Recent studies comparing RE, RDD, and CRD causal estimates have found that CRD reduces imprecision compared to RDD and also produces valid causal estimates at the treatment cutoff and also along all the rest of the assignment variable. The present study seeks to replicate these results, but with considerably smaller sample sizes. The power difference between RDD and CRD is replicated, but not the bias results either at the treatment cutoff or away from it. We conclude that CRD without large samples can be dangerous.

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Shape of wing wear fails to affect load lifting in common eastern bumble bees (Bombus impatiens) with experimental wing wear

Canadian Journal of Zoology ◽

10.1139/cjz-2014-0317 ◽

2015 ◽

Vol 93 (7) ◽

pp. 531-537 ◽

Cited By ~ 3

Author(s):

Jordan C. Roberts ◽

Ralph V. Cartar

Keyword(s):

Effect Size ◽

Maximum Load ◽

Bumble Bees ◽

Bombus Impatiens ◽

Detectable Effect ◽

Flight Performance ◽

Wingbeat Frequency ◽

Wing Area ◽

Irreversible Damage ◽

Wing Wear

Wing wear reflects the accumulation of irreversible damage to an insect’s wings over its lifetime and this damage should influence flight performance. In the case of bumble bees, flight seems robust to variation in wing-area asymmetry and air pressure, but not to loss of wing area. However, how the pattern of wing wear affects flight performance remains unstudied. In nature, wing wear typically occurs in a ragged and haphazard pattern along the wing’s trailing margin, a shape strikingly different from the straight cut applied in past studies. In this study, we test if shape of wing wear (implemented as four distinct treatments plus a control) affects maximum load-lifting capabilities and wingbeat frequency of worker common eastern bumble bees (Bombus impatiens Cresson, 1863). We found that shape of wing wear of 171 mg bees had no detectable effect on maximum load-lifting capability (detectable effect size = 18 mg) or on wingbeat frequency (detectable effect size = 15 Hz), but that loss of wing area reduced load-lifting capability and increased wingbeat frequency. The importance of wing area in explaining the load-lifting ability of bumble bees is reinforced in this study. But, paradoxically, shape of wing wear did not detectably affect lift generation, which is determined by unsteady aerodynamic forces in these lift-reliant insects.

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