In a study comparing the effects of two treatments, the propensity score is the probability of assignment to one treatment conditional on a subject's measured baseline covariates. Propensity-score matching is increasingly being used to estimate the effects of exposures using observational data. In the most common implementation of propensity-score matching, pairs of treated and untreated subjects are formed whose propensity scores differ by at most a pre-specified amount (the caliper width). There has been a little research into the optimal caliper width. We conducted an extensive series of Monte Carlo simulations to determine the optimal caliper width for estimating differences in means (for continuous outcomes) and risk differences (for binary outcomes). When estimating differences in means or risk differences, we recommend that researchers match on the logit of the propensity score using calipers of width equal to 0.2 of the standard deviation of the logit of the propensity score. When at least some of the covariates were continuous, then either this value, or one close to it, minimized the mean square error of the resultant estimated treatment effect. It also eliminated at least 98% of the bias in the crude estimator, and it resulted in confidence intervals with approximately the correct coverage rates. Furthermore, the empirical type I error rate was approximately correct. When all of the covariates were binary, then the choice of caliper width had a much smaller impact on the performance of estimation of risk differences and differences in means.
BACKGROUND: Scoping reviews are a relatively new approach to evidence synthesis and currently there exists little guidance regarding the decision to choose between a systematic review or scoping review approach when synthesising evidence. The purpose of this article is to clearly describe the differences in indications between scoping reviews and systematic reviews and to provide guidance for when a scoping review is (and is not) appropriate. RESULTS: Researchers may conduct scoping reviews instead of systematic reviews where the purpose of the review is to identify knowledge gaps, scope a body of literature, clarify concepts or to investigate research conduct. While useful in their own right, scoping reviews may also be helpful precursors to systematic reviews and can be used to confirm the relevance of inclusion criteria and potential questions. CONCLUSIONS: Scoping reviews are a useful tool in the ever increasing arsenal of evidence synthesis approaches. Although conducted for different purposes compared to systematic reviews, scoping reviews still require rigorous and transparent methods in their conduct to ensure that the results are trustworthy. Our hope is that with clear guidance available regarding whether to conduct a scoping review or a systematic review, there will be less scoping reviews being performed for inappropriate indications better served by a systematic review, and vice-versa.
We wish to test a simple hypothesis against a family of alternatives indexed by a one-dimensional parameter, θ. We use a test derived from the corresponding family of test statistics appropriate for the case when θ is given. Davies (1977) introduced this problem when these test statistics had normal distributions. The present paper considers the case when their distribution is chi-squared. The results are applied to the detection of a discrete frequency component of unknown frequency in a time series. In addition quick methods for finding approximate significance probabilities are given for both the normal and chi-squared cases and applied to the two-phase regression problem in the normal case.
Cronbach’s alpha is a statistic commonly quoted by authors to demonstrate that tests and scales that have been constructed or adopted for research projects are fit for purpose. Cronbach’s alpha is regularly adopted in studies in science education: it was referred to in 69 different papers published in 4 leading science education journals in a single year (2015)—usually as a measure of reliability. This article explores how this statistic is used in reporting science education research and what it represents. Authors often cite alpha values with little commentary to explain why they feel this statistic is relevant and seldom interpret the result for readers beyond citing an arbitrary threshold for an acceptable value. Those authors who do offer readers qualitative descriptors interpreting alpha values adopt a diverse and seemingly arbitrary terminology. More seriously, illustrative examples from the science education literature demonstrate that alpha may be acceptable even when there are recognised problems with the scales concerned. Alpha is also sometimes inappropriately used to claim an instrument is unidimensional. It is argued that a high value of alpha offers limited evidence of the reliability of a research instrument, and that indeed a very high value may actually be undesirable when developing a test of scientific knowledge or understanding. Guidance is offered to authors reporting, and readers evaluating, studies that present Cronbach’s alpha statistic as evidence of instrument quality.
Purpose The purpose of this paper is to provide a comprehensive, yet concise, overview of the considerations and metrics required for partial least squares structural equation modeling (PLS-SEM) analysis and result reporting. Preliminary considerations are summarized first, including reasons for choosing PLS-SEM, recommended sample size in selected contexts, distributional assumptions, use of secondary data, statistical power and the need for goodness-of-fit testing. Next, the metrics as well as the rules of thumb that should be applied to assess the PLS-SEM results are covered. Besides presenting established PLS-SEM evaluation criteria, the overview includes the following new guidelines: PLSpredict (i.e., a novel approach for assessing a model’s out-of-sample prediction), metrics for model comparisons, and several complementary methods for checking the results’ robustness. Design/methodology/approach This paper provides an overview of previously and recently proposed metrics as well as rules of thumb for evaluating the research results based on the application of PLS-SEM. Findings Most of the previously applied metrics for evaluating PLS-SEM results are still relevant. Nevertheless, scholars need to be knowledgeable about recently proposed metrics (e.g. model comparison criteria) and methods (e.g. endogeneity assessment, latent class analysis and PLSpredict), and when and how to apply them to extend their analyses. Research limitations/implications Methodological developments associated with PLS-SEM are rapidly emerging. The metrics reported in this paper are useful for current applications, but must always be up to date with the latest developments in the PLS-SEM method. Originality/value In light of more recent research and methodological developments in the PLS-SEM domain, guidelines for the method’s use need to be continuously extended and updated. This paper is the most current and comprehensive summary of the PLS-SEM method and the metrics applied to assess its solutions.
Abstract It is shown that, when two superposed fluids of different densities are accelerated in a direction perpendicular to their interface, this surface is stable or unstable according to whether the acceleration is directed from the heavier to the lighter fluid or vice versa. The relationship between the rate of development of the instability and the length of wave-like disturbances, the acceleration and the densities is found, and similar calculations are made for the case when a sheet of liquid of uniform depth is accelerated.
Current psychological theory and research affirm the positive affective and motivational consequences of having personal choice. These findings have led to the popular notion that the more choice, the better-that the human ability to manage, and the human desire for, choice is unlimited. Findings from 3 experimental studies starkly challenge this implicit assumption that having more choices is necessarily more intrinsically motivating than having fewer. These experiments, which were conducted in both field and laboratory settings, show that people are more likely to purchase gourmet jams or chocolates or to undertake optional class essay assignments when offered a limited array of 6 choices rather than a more extensive array of 24 or 30 choices. Moreover, participants actually reported greater subsequent satisfaction with their selections and wrote better essays when their original set of options had been limited. Implications for future research are discussed.
This study focused on the conditions under which job dissatisfaction will lead to creativity as an expression of voice. We theorized that useful feedback from coworkers, coworker helping and support, and perceived organizational support for creativity would each interact with job dissatisfaction and continuance commitment (commitment motivated by necessity) to result in creativity. In a sample of 149 employees, as hypothesized, employees with high job dissatisfaction exhibited the highest creativity when continuance commitment was high and when (1) useful feedback from coworkers, or (2) coworker helping and support, or (3) perceived organizational support for creativity was high.
We argue that the government-spending multiplier can be much larger than one when the zero lower bound on the nominal interest rate binds. The larger is the fraction of government spending that occurs while the nominal interest rate is zero, the larger is the value of the multiplier. After providing intuition for these results, we investigate the size of the multiplier in a dynamic, stochastic, general equilibrium model. In this model the multiplier e�ect is substantially larger than one when the zero bound binds. Our model is consistent with the behavior of key macro aggregates during the recent financial crisis. We thank the editor, Monika Piazzesi, Rob Shimer, and two anonymous referees for their
This paper addresses digital communication in a Rayleigh fading environment when the channel characteristic is unknown at the transmitter but is known (tracked) at the receiver. Inventing a codec architecture that can realize a significant portion of the great capacity promised by information theory is essential to a standout long-term position in highly competitive arenas like fixed and indoor wireless. Use (n <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</inf> , n <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</inf> ) to express the number of antenna elements at the transmitter and receiver. An (n, n) analysis shows that despite the n received waves interfering randomly, capacity grows linearly with n and is enormous. With n = 8 at 1% outage and 21-dB average SNR at each receiving element, 42 b/s/Hz is achieved. The capacity is more than 40 times that of a (1, 1) system at the same total radiated transmitter power and bandwidth. Moreover, in some applications, n could be much larger than 8. In striving for significant fractions of such huge capacities, the question arises: Can one construct an (n, n) system whose capacity scales linearly with n, using as building blocks n separately coded one-dimensional (1-D) subsystems of equal capacity? With the aim of leveraging the already highly developed 1-D codec technology, this paper reports just such an invention. In this new architecture, signals are layered in space and time as suggested by a tight capacity bound.
Binary classifiers are routinely evaluated with performance measures such as sensitivity and specificity, and performance is frequently illustrated with Receiver Operating Characteristics (ROC) plots. Alternative measures such as positive predictive value (PPV) and the associated Precision/Recall (PRC) plots are used less frequently. Many bioinformatics studies develop and evaluate classifiers that are to be applied to strongly imbalanced datasets in which the number of negatives outweighs the number of positives significantly. While ROC plots are visually appealing and provide an overview of a classifier's performance across a wide range of specificities, one can ask whether ROC plots could be misleading when applied in imbalanced classification scenarios. We show here that the visual interpretability of ROC plots in the context of imbalanced datasets can be deceptive with respect to conclusions about the reliability of classification performance, owing to an intuitive but wrong interpretation of specificity. PRC plots, on the other hand, can provide the viewer with an accurate prediction of future classification performance due to the fact that they evaluate the fraction of true positives among positive predictions. Our findings have potential implications for the interpretation of a large number of studies that use ROC plots on imbalanced datasets.
Nondetection of a species at a site does not imply that the species is absent unless the probability of detection is 1. We propose a model and likelihood-based method for estimating site occupancy rates when detection probabilities are <1. The model provides a flexible framework enabling covariate information to be included and allowing for missing observations. Via computer simulation, we found that the model provides good estimates of the occupancy rates, generally unbiased for moderate detection probabilities (>0.3). We estimated site occupancy rates for two anuran species at 32 wetland sites in Maryland, USA, from data collected during 2000 as part of an amphibian monitoring program, Frogwatch USA. Site occupancy rates were estimated as 0.49 for American toads (Bufo americanus), a 44% increase over the proportion of sites at which they were actually observed, and as 0.85 for spring peepers (Pseudacris crucifer), slightly above the observed proportion of 0.83.
Journal Article THE GENERALIZATION OF ‘STUDENT'S’ PROBLEM WHEN SEVERAL DIFFERENT POPULATION VARLANCES ARE INVOLVED Get access B. L. WELCH, B.A., PH.D. B. L. WELCH, B.A., PH.D. Search for other works by this author on: Oxford Academic Google Scholar Biometrika, Volume 34, Issue 1-2, January 1947, Pages 28–35, https://doi.org/10.1093/biomet/34.1-2.28 Published: 01 January 1947
A method is proposed for estimating intra-block and inter-blook weights in the analysis of incomplete block designs with block sizes not necessarily equal. The method consists of maximizing the likelihood, not of all the data, but of a set of selected error contrasts. When block sizes are equal results are identical with those obtained by the method of Nelder (1968) for generally balanced designs. Although mainly concerned with incomplete block designs the paper also gives in outline an extension of the modified maximum likelihood procedure to designs with a more complicated block structure.
A Wall Street Journal and Businessweek bestseller. Named by Fast Company as one of the most influential leadership books in its Leadership Hall of Fame. An innovation classic. From Steve Jobs to Jeff Bezos, Clay Christensens work continues to underpin todays most innovative leaders and organizations. The bestselling classic on disruptive innovation, by renowned author Clayton M. Christensen. His work is cited by the worlds best-known thought leaders, from Steve Jobs to Malcolm Gladwell. In this classic bestsellerone of the most influential business books of all timeinnovation expert Clayton Christensen shows how even the most outstanding companies can do everything rightyet still lose market leadership. Christensen explains why most companies miss out on new waves of innovation. No matter the industry, he says, a successful company with established products will get pushed aside unless managers know how and when to abandon traditional business practices. Offering both successes and failures from leading companies as a guide, The Innovators Dilemma gives you a set of rules for capitalizing on the phenomenon of disruptive innovation. Sharp, cogent, and provocativeand consistently noted as one of the most valuable business ideas of all time The Innovators Dilemma is the book no manager, leader, or entrepreneur should be without.
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For the first time in the twentieth century most adults in many innercity ghetto neighborhoods are not working in a typical week. The disappearance of work has adversely affected not only individuals, families, and neighborhoods, but the social life of the city at large as well. Inner-city joblessness is a severe problem that is often overlooked or obscured when the focus is placed mainly on poverty and its consequences. Despite increases in the concentration of poverty since 1970, inner cities have always featured high levels of poverty, but the current levels of joblessness in some neighborhoods are unprecedented. The consequences of high neighborhood joblessness are more devastating than those of high neighborhood poverty. A neighborhood in which people are poor but employed is different from a neighborhood in which people are poor and jobless. Many of today's problems in the inner-city ghetto neighborhoodscrime, family dissolution, welfare, low levels of social organization, and so onare fundamentally a consequence of the disappearance of work. The disappearance of work and the growth of related problems in the ghetto have aggravated an already tense racial situation in urban areas. Our nation's response to racial discord in the central city and to the growing racial divide between the city and the suburbs has been disappointing. In discussing these problems we have a tendency to engage in the kind of rhetoric that exacerbates, rather than alleviates, urban and metropolitan racial tensions. Ever since the 1992 Los Angeles riot, the media have focused heavily on the factors that divide rather than those that unite racial groups. Emphasis on racial division peaked in 1995 following the jury's verdict in the 0. J. Simpson murder trial. Before
Abstract In applied problems it is common to specify a model for the conditional mean of a response given a set of regressors. A subset of the regressors may be missing for some study subjects either by design or happenstance. In this article we propose a new class of semiparametric estimators, based on inverse probability weighted estimating equations, that are consistent for parameter vector α0 of the conditional mean model when the data are missing at random in the sense of Rubin and the missingness probabilities are either known or can be parametrically modeled. We show that the asymptotic variance of the optimal estimator in our class attains the semiparametric variance bound for the model by first showing that our estimation problem is a special case of the general problem of parameter estimation in an arbitrary semiparametric model in which the data are missing at random and the probability of observing complete data is bounded away from 0, and then deriving a representation for the efficient score, the semiparametric variance bound, and the influence function of any regular, asymptotically linear estimator in this more general estimation problem. Because the optimal estimator depends on the unknown probability law generating the data, we propose locally and globally adaptive semiparametric efficient estimators. We compare estimators in our class with previously proposed estimators. We show that each previous estimator is asymptotically equivalent to some, usually inefficient, estimator in our class. This equivalence is a consequence of a proposition stating that every regular asymptotic linear estimator of α0 is asymptotically equivalent to some estimator in our class. We compare various estimators in a small simulation study and offer some practical recommendations.
As governmental activity has expanded, scholars have been increasingly inclined to suggest that the structure of public policies has an important influence on patterns of political change. Yet research on policy feedback is mostly anecdotal, and there has so far been little attempt to develop more general hypotheses about the conditions under which policies produce politics. Drawing on recent research, this article suggests that feedback occurs through two main mechanisms. Policies generate resources and incentives for political actors, and they provide those actors with information and cues that encourage particular interpretations of the political world. These mechanisms operate in a variety of ways, but have significant effects on government elites, interest groups, and mass publics. By investigating how policies influence different actors through these distinctive mechanisms, the article outlines a research agenda for moving from the current focus on illustrative case studies to the investigation of broader propositions about how and when policies are likely to be politically consequential.
Species Meet is a breathtaking meditation on the intersection between humankind dog, philosophy science, macro micro cultures.-Cameron Woo, Publisher of Bark magazine In 2006, about 69 million U.S. households had pets, giving homes to around 73.9 million dogs, 90.5 million cats, 16.6 million birds, spending over $38 billion dollars on animals. As never before in history, our pets are truly members of the family. But the notion of companion speciesd-knotted from human beings, animals other organisms, landscapes, technologies-includes much more than companion animals.d In When Species Meet, Donna J. Haraway digs into this larger phenomenon to contemplate the interactions of humans with many kinds of critters, especially with those called domestic. At the heart of the book are her experiences in agility training with her dogs Cayenne Roland, but Haraway's vision here also encompasses wolves, chickens, cats, baboons, sheep, microorganisms, whales wearing video cameras. From designer pets to lab animals to trained therapy dogs, she deftly explores philosophical, cultural, biological aspects of animal-human encounters. In this deeply personal yet intellectually groundbreaking work, Haraway develops the idea of species, those who meet break bread together but not without some indigestion. A great deal is at stake in such meetings,she writes, and outcomes are not guaranteed. There is no assured happy or unhappy ending-socially, ecologically, or scientifically. There is only the chance for getting on together with some grace.d Ultimately, she finds that respect, curiosity, knowledge spring from animal-human associations work powerfully against ideas about human exceptionalism. One of the founders of the posthumanities, Donna J. Haraway is professor in the History of Consciousness Department at the University of California, Santa Cruz. Author of many books widely read essays, including Companion Species Manifesto: Dogs, People, Significant Otherness the now-classic essay The Cyborg Manifesto,she received the J. D. Bernal Prize in 2000, a lifetime achievement award from the Society for Social Studies in Science.