Statistical power to detect main and interactive effects on the attributes of small-mammal populations

1999 ◽  
Vol 77 (1) ◽  
pp. 68-73 ◽  
Author(s):  
Eric M Schauber ◽  
W Daniel Edge
Keyword(s):  
Statistical Power ◽  
Statistical Tests ◽  
Interactive Effects ◽  
Natural Systems ◽  
Real Effects ◽  
Treatment Variation ◽  
Higher Power ◽  
Using Data ◽  
Main Effects ◽  
Response Variables

Statistical power is an important consideration in the design of experiments, because resources invested in an experiment may be wasted if it is unlikely to produce statistically significant results when real effects or differences exist. Using data from toxicological experiments on seminatural populations of small mammals, we examined the power of statistical tests for main and interactive effects. Our objectives were to evaluate the efficacy of actively reducing within-treatment variation in order to increase power and compare the power provided by several response variables commonly measured in population studies. Controlling population size (N) before treatment increased power to detect effects on N but decreased power to detect effects on population growth (r). For a specified reduction in N, r provided higher power than N. Fractional measures of recruitment generally provided low power, especially when N was low (<20 animals). Power to detect an interaction of two adverse treatments depended on the magnitudes of their main effects, as well as the magnitude of interactive effects. Estimating or predicting effect size is more complex and difficult for interactive effects than for main effects. We conclude that researchers can increase the probability of detecting real effects by choosing response variables with relatively low inherent variability. However, efforts to actively reduce within-treatment variation may have unanticipated repercussions in natural systems.

The influence of prescriber and patient gender on the prescription of benzodiazepines: results from the Florida Medicaid Dataset

CNS Spectrums ◽  
2021 ◽  
pp. 1-5
Author(s):  
Leanna M. W. Lui ◽  
Yena Lee ◽  
Orly Lipsitz ◽  
Nelson B. Rodrigues ◽  
Hartej Gill ◽  
...  
Keyword(s):  
The United States ◽  
Sociodemographic Factors ◽  
Cross Sectional Study ◽  
Cross Sectional ◽  
Assistance Program ◽  
Patient Gender ◽  
Prescription Rates ◽  
Male Patients ◽  
Using Data ◽  
Main Effects

Abstract Background Benzodiazepine (BZD) prescription rates have increased over the past decade in the United States. Available literature indicates that sociodemographic factors may influence diagnostic patterns and/or prescription behaviour. Herein, the aim of this study is to determine whether the gender of the prescriber and/or patient influences BZD prescription. Methods Cross-sectional study using data from the Florida Medicaid Managed Medical Assistance Program from January 1, 2018 to December 31, 2018. Eligible recipients ages 18 to 64, inclusive, enrolled in the Florida Medicaid plan for at least 1 day, and were dually eligible. Recipients either had a serious mental illness (SMI), or non-SMI and anxiety. Results Total 125 463 cases were identified (i.e., received BZD or non-BZD prescription). Main effect of patient and prescriber gender was significant F(1, 125 459) = 0.105, P = 0 .745, partial η2 < 0.001. Relative risk (RR) of male prescribers prescribing a BZD compared to female prescribers was 1.540, 95% confidence intervals (CI) [1.513, 1.567], whereas the RR of male patients being prescribed a BZD compared to female patients was 1.16, 95% CI [1.14, 1.18]. Main effects of patient and prescriber gender were statistically significant F(1, 125 459) = 188.232, P < 0.001, partial η2 = 0.001 and F(1, 125 459) = 349.704, P < 0.001, partial η2 = 0.013, respectively. Conclusions Male prescribers are more likely to prescribe BZDs, and male patients are more likely to receive BZDs. Further studies are required to characterize factors that influence this gender-by-gender interaction.

Constrained and Unconstrained Partial Adjacent Category Logit Models for Ordinal Response Variables

2015 ◽  
Vol 47 (2) ◽  
pp. 169-206 ◽  
Author(s):  
Andrew S. Fullerton ◽  
Jun Xu
Keyword(s):  
General Social Survey ◽  
Estimation Method ◽  
Logit Models ◽  
Proportional Odds ◽  
Social Survey ◽  
Partial Model ◽  
Ordinal Response ◽  
Proportional Odds Assumption ◽  
Using Data ◽  
Response Variables

Adjacent category logit models are ordered regression models that focus on comparisons of adjacent categories. These models are particularly useful for ordinal response variables with categories that are of substantive interest. In this article, we consider unconstrained and constrained versions of the partial adjacent category logit model, which is an extension of the traditional model that relaxes the proportional odds assumption for a subset of independent variables. In the unconstrained partial model, the variables without proportional odds have coefficients that freely vary across cutpoint equations, whereas in the constrained partial model two or more of these variables have coefficients that vary by common factors. We improve upon an earlier formulation of the constrained partial adjacent category model by introducing a new estimation method and conceptual justification for the model. Additionally, we discuss the connections between partial adjacent category models and other models within the adjacent approach, including stereotype logit and multinomial logit. We show that the constrained and unconstrained partial models differ only in terms of the number of dimensions required to describe the effects of variables with nonproportional odds. Finally, we illustrate the partial adjacent category logit models with empirical examples using data from the international social survey program and the general social survey.

The Roles of Disliking, Deservingness, and Envy in Predicting Schadenfreude

2020 ◽  
pp. 003329412092135
Author(s):  
Keegan D. Greenier
Keyword(s):  
Pilot Study ◽  
Interactive Effects ◽  
Large Pool ◽  
Single Study ◽  
Benign Envy ◽  
Main Effects ◽  
First Time

Schadenfreude (pleasure about another’s misfortune) was studied using written scenarios that were manipulated to include elements that elicited disliking of the target, envy of the target, and/or deservingness of the misfortune. This was the first time all the three predictors were included in a single study, allowing for a test of their possible interactive effects. Study 1 created a large pool of scenarios based on a pilot study and had participants rate them regarding how much disliking, deservingness, or envy was felt. The eight scenarios that were most effective in eliciting the various combinations of predictors were then used in Study 2 to test for schadenfreude reactions. Results revealed strong main effects for disliking and deservingness. Interactions showed that disliking attenuated the effect of deservingness, especially for female participants. Finally, further evidence was found that malicious but not benign envy predicted schadenfreude.

scholarly journals Using machine learning to predict extreme events in complex systems

2019 ◽  
Vol 117 (1) ◽  
pp. 52-59 ◽  
Author(s):  
Di Qi ◽  
Andrew J. Majda
Keyword(s):  
Dynamical Systems ◽  
Learning Strategies ◽  
Extreme Events ◽  
Water Waves ◽  
Extreme Values ◽  
Training Data ◽  
Partition Functions ◽  
Grand Challenge ◽  
Natural Systems ◽  
Using Data

Extreme events and the related anomalous statistics are ubiquitously observed in many natural systems, and the development of efficient methods to understand and accurately predict such representative features remains a grand challenge. Here, we investigate the skill of deep learning strategies in the prediction of extreme events in complex turbulent dynamical systems. Deep neural networks have been successfully applied to many imaging processing problems involving big data, and have recently shown potential for the study of dynamical systems. We propose to use a densely connected mixed-scale network model to capture the extreme events appearing in a truncated Korteweg–de Vries (tKdV) statistical framework, which creates anomalous skewed distributions consistent with recent laboratory experiments for shallow water waves across an abrupt depth change, where a remarkable statistical phase transition is generated by varying the inverse temperature parameter in the corresponding Gibbs invariant measures. The neural network is trained using data without knowing the explicit model dynamics, and the training data are only drawn from the near-Gaussian regime of the tKdV model solutions without the occurrence of large extreme values. A relative entropy loss function, together with empirical partition functions, is proposed for measuring the accuracy of the network output where the dominant structures in the turbulent field are emphasized. The optimized network is shown to gain uniformly high skill in accurately predicting the solutions in a wide variety of statistical regimes, including highly skewed extreme events. The technique is promising to be further applied to other complicated high-dimensional systems.

scholarly journals NotchPUF: Printed Circuit Board PUF Based on Microstrip Notch Filter

Cryptography ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 11
Author(s):  
Mitchell Martin ◽  
Jim Plusquellic
Keyword(s):  
Printed Circuit Boards ◽  
Printed Circuit Board ◽  
Statistical Tests ◽  
Notch Filter ◽  
Circuit Board ◽  
Circuit Boards ◽  
Printed Circuit ◽  
In Series ◽  
Commercial Off The Shelf ◽  
Using Data

Physical Unclonable Functions (PUFs) are primitives that are designed to leverage naturally occurring variations to produce a random bitstring. Current PUF designs are typically implemented in silicon or utilize variations found in commercial off-the-shelf (COTS) parts. Because of this, existing designs are insufficient for the authentication of Printed Circuit Boards (PCBs). In this paper, we propose a novel PUF design that leverages board variations in a manufactured PCB to generate unique and stable IDs for each PCB. In particular, a single copper trace is used as a source of randomness for bitstring generation. The trace connects three notch filter structures in series, each of which is designed to reject specific but separate frequencies. The bitstrings generated using data measured from a set of PCBs are analyzed using statistical tests to illustrate that high levels of uniqueness and randomness are achievable.

scholarly journals Temporal and spatial changes of rainfall and streamflow in the Upper Tekezē–Atbara river basin, Ethiopia

2017 ◽  
Vol 21 (4) ◽  
pp. 2127-2142 ◽  
Author(s):  
Tesfay G. Gebremicael ◽  
Yasir A. Mohamed ◽  
Pieter v. Zaag ◽  
Eyasu Y. Hagos
Keyword(s):  
Change Point ◽  
Statistical Tests ◽  
Catchment Management ◽  
Trend Analyses ◽  
Temporal And Spatial Variability ◽  
Spatial Changes ◽  
Changing Patterns ◽  
Temporal And Spatial ◽  
Using Data ◽  
Streamflow Trends

Abstract. The Upper Tekezē–Atbara river sub-basin, part of the Nile Basin, is characterized by high temporal and spatial variability of rainfall and streamflow. In spite of its importance for sustainable water use and food security, the changing patterns of streamflow and its association with climate change is not well understood. This study aims to improve the understanding of the linkages between rainfall and streamflow trends and identify possible drivers of streamflow variabilities in the basin. Trend analyses and change-point detections of rainfall and streamflow were analysed using Mann–Kendall and Pettitt tests, respectively, using data records for 21 rainfall and 9 streamflow stations. The nature of changes and linkages between rainfall and streamflow were carefully examined for monthly, seasonal and annual flows, as well as indicators of hydrologic alteration (IHA). The trend and change-point analyses found that 19 of the tested 21 rainfall stations did not show statistically significant changes. In contrast, trend analyses on the streamflow showed both significant increasing and decreasing patterns. A decreasing trend in the dry season (October to February), short season (March to May), main rainy season (June to September) and annual totals is dominant in six out of the nine stations. Only one out of nine gauging stations experienced significant increasing flow in the dry and short rainy seasons, attributed to the construction of Tekezē hydropower dam upstream this station in 2009. Overall, streamflow trends and change-point timings were found to be inconsistent among the stations. Changes in streamflow without significant change in rainfall suggests factors other than rainfall drive the change. Most likely the observed changes in streamflow regimes could be due to changes in catchment characteristics of the basin. Further studies are needed to verify and quantify the hydrological changes shown in statistical tests by identifying the physical mechanisms behind those changes. The findings from this study are useful as a prerequisite for studying the effects of catchment management dynamics on the hydrological variabilities in the basin.

‘PLEASE LEAD ME, MY COMMITMENT IS LOW’: INTERACTIVE EFFECTS OF COMMITMENT AND LEADERSHIP ON INNOVATIVE BEHAVIOUR

2019 ◽  
Vol 23 (02) ◽  
pp. 1950015 ◽  
Author(s):  
PETER KHAOLA ◽  
DAVID COLDWELL
Keyword(s):  
Affective Commitment ◽  
Theory And Practice ◽  
Interactive Effects ◽  
Public And Private ◽  
Management Level ◽  
Innovation Research ◽  
Innovative Behaviour ◽  
Innovative Work ◽  
Main Effects ◽  
The Relationship

Even though the effects of leadership and affective commitment on innovative work behaviours (IWBs) have been thoroughly researched, little is known about the interactive effects of these factors on IWBs. Based on data collected from 263 respondents from public and private organisations in Lesotho, the present study examines if affective commitment moderates the relationship between leadership and IWB. Drawing on literatures across management and innovation research domains, the study proposes and finds evidence that affective commitment moderates the relationship between leadership and IWB such that the relationship is stronger for affectively committed employees, while being relatively weaker for less affectively committed employees. The results also reveal that while leadership and management level have the main effects on IWB, affective commitment has no effect on IWB. Overall, the study responds to calls for examining the joint effects of person and context characteristics on IWBs. Drawing on our results, we discuss implications for theory and practice.

scholarly journals Effective Analysis of Interactive Effects with Non-Normal Data Using the Aligned Rank Transform, ARTool and SAS® University Edition

Horticulturae ◽  
2019 ◽  
Vol 5 (3) ◽  
pp. 57 ◽  
Author(s):  
Edward Durner
Keyword(s):  
Type I Error ◽  
Interactive Effects ◽  
Type I ◽  
Rank Transform ◽  
Parametric Testing ◽  
Aligned Rank ◽  
Departure From Normality ◽  
Main Effects ◽  
Horticultural Research ◽  
Non Parametric

Most statistical techniques commonly used in horticultural research are parametric tests that are valid only for normal data with homogeneous variances. While parametric tests are robust when the data ‘slightly’ deviate from normality, a significant departure from normality leads to reduced power and the probability of a type I error increases. Transformations often used to normalize non-normal data can be time consuming, cumbersome and confusing and common non-parametric tests are not appropriate for evaluating interactive effects common in horticultural research. The aligned rank transformation allows non-parametric testing for interactions and main effects using standard ANOVA techniques. This has not been widely adapted due to its rigorous mathematical nature, however, a downloadable (ARTool) is now available, which performs the math needed for the transformation. This study provides step-by-step instructions for integrating ARTool with the free edition of SAS (SAS University Edition) in an easily employed method for testing normality, transforming data with aligned ranks, and analysing data using standard ANOVAs.

A Factor Interactive Investigation of Mail Survey Response Rates from a Commercial Population

1977 ◽  
Vol 14 (1) ◽  
pp. 108-111 ◽  
Author(s):  
Milton M. Pressley ◽  
William L. Tullar
Keyword(s):  
Response Rate ◽  
Psychological Impact ◽  
Mail Survey ◽  
Threshold Value ◽  
The Other ◽  
Interactive Effects ◽  
Monetary Incentives ◽  
Monetary Value ◽  
Commercial Population ◽  
Main Effects

The results of a factorial experiment showed that a 10¢ incentive significantly increased the response rate from the commercial population surveyed by mail. No significant main effects were noted for the other factors tested, questionnaire color and cartoon illustrations included on the questionnaire. No significant interactive effects were found. The results of this investigation, in combination with those of earlier investigations, support the hypothesis that the importance of monetary inducements stems primarily from the psychological impact of receiving money (as opposed to the monetary value itself). Thus the hypothesis can be generalized with greater confidence to commercial populations. However, the results imply that there apparently is a threshold value for increasing response with monetary incentives which is lower for commercial populations (10¢) than it is for general public populations (25¢).

scholarly journals Shock Transmission Through Cross-Border Bank Lending: Credit and Real Effects

2019 ◽  
Vol 33 (10) ◽  
pp. 4839-4882 ◽  
Author(s):  
Galina Hale ◽  
Tümer Kapan ◽  
Camelia Minoiu
Keyword(s):  
Bank Lending ◽  
Banking Crises ◽  
Financial Networks ◽  
Financial Shocks ◽  
Real Effects ◽  
Cross Border ◽  
International Bank ◽  
Idiosyncratic Shocks ◽  
Shock Transmission ◽  
Using Data

Abstract We study the transmission of financial shocks across borders through international bank connections. Using data on cross-border interbank loans among 6,000 banks during 1997–2012, we estimate the effect of asset-side exposures to banks in countries experiencing systemic banking crises on profitability, credit, and the performance of borrower firms. Crisis exposures reduce bank returns and tighten credit conditions for borrowers, constraining investment and growth. The effects are larger for foreign borrowers, including in countries not experiencing banking crises. Our results document the extent of cross-border crisis transmission, but also highlight the resilience of financial networks to idiosyncratic shocks.

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