Low, moderate, and high handicap golfers, while wearing glasses with a blinder on the side, attempted 9 putts differing in length from 5 to 21 ft under timed (less than 3.5s from grounding of club to initiation of back swing) and untimed conditions in a counterbalanced design. Confidence ratings were taken prior to and following each putt. The results revealed a significant condition by handicap group interaction (p=.021). The lower handicap group had a more consistent and lower initiation interval duration than did the moderate and high handicap players. Post interviews determined that 33 of the 35 golfers felt more comfortable in the untimed condition. However, golfers' confidence levels were not significantly different in the untimed condition as compared to the timed condition.

Comparative experiments, in which subjects are randomized to one of two treatments, are performed often. There is no shortage of papers testing whether a treatment effect exists and providing confidence intervals for the magnitude of this effect. While it is well understood that the object and scope of inference for an experiment will depend on what assumptions are made, these entities are not always clearly presented. We have proposed one possible method, which is based on the ideas of Jerzy Neyman, that can be used for constructing confidence intervals in a comparative experiment. The resulting intervals, referred to as Neyman-type confidence intervals, can be applied in a wide range of cases. Special care is taken to note which assumptions are made and what object and scope of inference are being investigated. We have presented a notation that highlights which parts of a problem are being treated as random. This helps ensure the focus on the appropriate scope of inference. The Neyman-type confidence intervals are compared to possible alternatives in two different inference settings: one in which inference is made about the units in the sample and one in which inference is made about units in a fixed population. A third inference setting, one in which inference is made about a process distribution, is also discussed. It is stressed that certain assumptions underlying this third type of inference are unverifiable. When these assumptions are not met, the resulting confidence intervals may cover their intended target well below the desired rate. Through simulation, we demonstrate that the Neyman-type intervals have good coverage properties when inference is being made about a sample or a population. In some cases the alternative intervals are much wider than necessary on average. Therefore, we recommend that researchers consider using our Neyman-type confidence intervals when carrying out inference about a sample or a population as it may provide them with more precise intervals that still cover at the desired rate.

O objetivo deste trabalho é averiguar a existência de incremento de acurácia nos modelos de previsão das diferentes categorias de consumo das famílias nos EUA ao se considerar a incerteza macroeconômica como variável explicativa. Grande parte dos trabalhos existentes na literatura consideram o índice da pesquisa de sentimento do consumidor da Universidade de Michigan ou a confiança do consumidor do Conference Board como variáveis alternativas capazes de antecipar o comportamento do consumo das famílias. Como se tratam de entrevistas que podem carregar parcialidade nas respostas e que não estão estritamente ligadas aos movimentos da incerteza, propomos a utilização de uma medida que agregue econometricamente as variações da incerteza macroeconômica, de tal forma que nossos modelos contenham informações mais refinadas sobre o comportamento da economia. A proposta e comparar o poder preditivo de quatro grupos de modelos econométricos para três horizontes temporais distintos (um, três e doze meses à frente). Para tal, consideramos a utilização do método de avaliação conjunta de superioridade preditiva, o Model Confidence Set. Os resultados obtidos apontam para a existência de contribuição preditiva ao incluir uma variável de incerteza macroeconômica para a previsão do consumo, em especial nos modelos de previsão um passo (mês) à frente. / The aim of this work is to verify the existence of an increase in forecasting models accuracy of different categories of household consumption in USA when considering macroeconomic uncertainty as an explanatory variable. Much of the work in the literature considers the University of Michigan Consumer Sentiment Survey Index or Conference Board Consumer Confidence as alternative variables capable of anticipating household consumption behavior. Because these indexes are composed of interviews that may carry a certain amount of bias in responses and are not strictly linked to the movements of uncertainty, we propose the use of a measure that econometrically adds variations of macroeconomic uncertainty, so that our models contain more refined information on the behavior of the economy. The proposal is to compare the predictive power of four groups of econometric models for three distinct time horizons (one, three and twelve months ahead). For this, we consider the use of the joint evaluation method of predictive superiority, Model Confidence Set. The results obtained point to the existence of a predictive contribution by including a macroeconomic uncertainty variable for consumption forecast, especially in the one step (month) ahead forecast models.

The study addresses whether differently ordered accounts receivable workprograms and task experience relate to differences in judgments, confidence levels, and recall ability. The study also assesses how treated and untreated inexperienced and experienced auditors store and recall accounts receivable workprogram steps in memory in a laboratory environment. Additionally, the question whether different levels of experienced auditors can effectively be manipulated is also addressed.

Confidence distributions (CDs), which provide evidence across all levels of significance, are receiving increasing attention, especially in meta-analysis. Meta-analyses allow independent study results to be combined to produce one overall conclusion and are particularly useful in public health and medicine. For studies with binary outcomes that are rare, many traditional meta-analysis methods often fail (Sutton et al. 2002; Efthimiou 2018; Liu et al. 2018; Liu 2019; Hunter and Schmidt 2000; Kontopantelis et al. 2013). Zabriskie et al. (2021b) develop a permutation-based method to analyze such data when study treatment effects vary beyond what is expected by chance. In this work, we prove that this method can be considered a CD. Additionally, we develop two new metrics to assess a CD's relative performance.

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Few general dentists feel comfortable treating very young children 0-5-years old due to inadequate training and exposure. Over the past few years, there is an increasing demand on providers to be culturally competent and meet the health needs of the culturally diverse population. OBJECTIVE: Assess the gained knowledge, perception and confidence in providing clinical dental care to vulnerable populations, pregnant adolescents and to very young children 0-5-years old following the enhancement of the predoctoral pediatric dental curriculum and training which was aimed to prepare future practitioners to be culturally competent in providing pediatric dental care to the current culturally diverse population. METHODS: This is a retrospective cross-sectional analysis conducted among the predoctoral students including the Doctor of Dental Medicine-(DMD) and Advanced Standing-(AS) who underwent pediatric dental training between 2017-2022 at Boston University Henry M. Goldman School of Dental Medicine, Boston, Massachusetts. Predoctoral students participated in the pre/post training surveys of the implemented didactic training program in cultural competency and oral health literacy lectures. The students completed questionnaires on their knowledge and confidence level on treating children 0-5-years old following the novel simulation scenario discussion after the Haptic simulator training and following clinical training in the pediatric dental clinic. Descriptive statistics were calculated, univariate and multivariate analysis were used to analyze the differences in the level of knowledge gained by program type, year of training and demographic characteristics such as age and gender. Statistical significance was set at p-value<0.05. RESULTS: The cultural competency training improved the students’ knowledge and perception. DMD-students performed better to have a higher level of knowledge in the post training survey compared to AS-students (OR=4.724;p<0.001). Based on the post training questionnaires, the haptic simulator session and novel simulation scenarios increased the students’ knowledge and confidence to treat pediatric patients. Student’s confidence to treat children 0-5-years and pregnant adolescents improved after completing the trainings. CONCLUSION: The new enhanced training program increased the predoctoral students’ knowledge and confidence to treat children 0-5-years. This can be beneficial when used in dental departments to support predoctoral graduates to be culturally competent who can be better prepared to manage the diverse population.