Overcoming barriers to time-saving: reminders of future busyness encourage consumers to buy time

Spending money on time saving purchases improves happiness. Yet, people often fail to spend their money in this way. Because most people believe that the future will be less busy than the present, they may underweight the value of these purchases. We examine the impact of debiasing this previously unexplored barrier of consumer decisions to ‘buy time’ in a field experiment with a US-based sharing economy (N = 78,726). Prompting people to think that they will be as busy in the future as they are today increased the likelihood that customers would both open the email and click a link to purchase various services. In sum, making the future feel as busy as the present encourages individuals to buy future time.     

Consistency and robustness properties of the S-nonnegative garrote estimator

This paper concerns a robust variable selection method in multiple linear regression: the robust S-nonnegative garrote variable selection method. In this paper the consistency of the method, both in terms of estimation and in terms of variable selection, is established. Moreover, the robustness properties of the method are further investigated by providing a lower bound for the breakdown point, and by deriving the influence function. The provided expressions nicely reveal the impact that the choice of an initial estimator has on the robustness properties of the variable selection method. Illustrative examples of influence functions for the S-nonnegative garrote as well as for the original (non-robust) nonnegative garrote variable selection method are provided.     

An algorithm for the multivariate group lasso with covariance estimation

We study a group lasso estimator for the multivariate linear regression model that accounts for correlated error terms. A block coordinate descent algorithm is used to compute this estimator. We perform a simulation study with categorical data and multivariate time series data, typical settings with a natural grouping among the predictor variables. Our simulation studies show the good performance of the proposed group lasso estimator compared to alternative estimators. We illustrate the method on a time series data set of gene expressions.     

On the relationship between the sample size and the number of variables in a linear regression model

The problem of determining the number of variables to be included in the linear regression model is considered under the assumption that the dependent and independent variables have a joint normal distribution. It is shown that for a given sample size n there exists an optimal number k₀ (0 ≤ k₀ < n-2) of variables among all independent variables in the model, such that the expectation of the mean squared error corresponding to the prediction equation with k₀ variables is minimal.Application of this result to ustepwise procedures is discussed.     

A clustering cure rate model with application to a sealant study

In this paper, the destructive negative binomial (DNB) cure rate model with a latent activation scheme [V. Cancho, D. Bandyopadhyay, F. Louzada, and B. Yiqi, The DNB cure rate model with a latent activation scheme, Statistical Methodology 13 (2013b), pp. 48–68] is extended to the case where the observations are grouped into clusters. Parameter estimation is performed based on the restricted maximum likelihood approach and on a Bayesian approach based on Dirichlet process priors. An application to a real data set related to a sealant study in a dentistry experiment is considered to illustrate the performance of the proposed model.     

How feedback about leadership potential impacts ambition,organizational commitment,and performance

In the present research we report results from two experimental studies that examine how feedback about leadership potential impacts leadership ambition, organizational commitment, and performance. Study 1 used an experimental vignette methodology that controls for prior performance. Results show that individuals who receive feedback that they have low potential to be a future leader have lower ambition and organizational commitment relative to those who receive feedback that they have high potential to be a future leader. Study 2 provides evidence of the causal behavioral effects of feedback about leadership potential using a real task effort environment. Results show that participants informed to be unlikely future leaders display lower performance in a subsequent task than participants informed to be likely future leaders. The findings from the two studies demonstrate that information about leadership potential affects subsequent ambition to become leaders as well as performance. We discuss the implications of these findings for the importance of followership, talent management, and leadership succession.     

英语四级是否与学位脱钩的调查报告———以石家庄铁道学院为例

近年来,关于大学英语四级与学位是否脱钩的问题出现了激烈的争论。通过对大学英语四级考试的回顾以及对出现问题的思考,并对石家庄铁道学院180名学生进行了关于英语四级与学位是否脱钩的调查。采取了实证性研究,得出结论,并就下一步的英语教学提出了相应的对策。     

Latent class piecewise linear trajectory modelling for short-term cognition responses after chemotherapy for breast cancer patients

This paper investigates the impact of chemotherapy on cognitive function of breast cancer patients and whether this response is homogeneous for all patients. Latent class piecewise linear trajectory (growth) models were employed to describe changes and identify subgroups in three Auditory Verbal Learning Test measures (learning, immediate retention and delayed recall) in 130 breast cancer patients taken at three time periods: before chemotherapy and 1 and 6 months post-chemotherapy. Two distinct subgroups of women exhibiting different patterns of response were identified for learning and delayed recall and three for immediate retention. The groups differed in level (intercept) at 1 month post-chemotherapy and patterns of decline and recovery. Binomial and multinomial logistic regressions on the latent classes found that age, initial National Adult Reading Test (NART)-predicted IQ, stage of cancer and the initial Functional Assessment of Cancer Therapy-Breast subscale (or subsets thereof) to be significant predictors of classes.