Analysing change in clinical trials using quasi-likelihoods

In clinical trials, investigations focus upon whether a treatment affects a measured outcome. Data often collected include pre- and post-treatment measurements on each patient and an analysis of the change in the outcome is typically performed to determine treatment efficacy. Absolute change and relative change are frequently selected as the outcome. In selecting from these two measures, the analyst makes implicit assumptions regarding the mean and variance-mean relationship of the data. Some have provided ad hoc guidelines for selecting between the two measures. We present a more rigorous means of investigating change using quasi-likelihoods. We show that both absolute change and relative change are special cases of the specified quasi-likelihood model. A cystic fibrosis example is provided.     

Why is Six Sigma so successful?

There can be little doubt that Motorola, General Electric, Black and Decker, Allied Signal (now Honeywell), ABB and Bombardier, have achieved impressive business performance in recent years. Their annual reports document this success. Furthermore, in several cases, the Annual Report clearly attributes this success to having followed a Six Sigma strategy. Not surprisingly, many other companies wish to learn what Six Sigma can do for them, and their first question is 'What exactly is Six Sigma?'. Unfortunately it is rather difficult, if not impossible, to define Six Sigma in one or two sentences. This paper identifies the essential elements of Six Sigma. Some are obvious, such as the extensive use of statistical techniques by employees known as Blackbelts. However, other more subtle, but very important, features of Six Sigma are concealed within the business culture of these successful companies. It is clear to those who have participated in this success, that any company embarking on Six Sigma will not succeed if it focuses on statistics whilst failing to develop a supporting culture.     

基于RAM的我国财险公司效率与偿付能力关系研究

 保险公司有不同的利益主体,投资者和公司管理者关注的重点是公司效率,而投保人和监管机构关注的核心是保险公司的偿付能力,那么效率与偿付能力是否存在冲突,或者说,监管机构的偿付能力约束是否影响公司效率以及影响程度究竟如何,是业界和学术界关注的主要内容。本文从金融中介的视角,考虑不同利益主体,把偿付能力作为一产出指标,通过分析该指标的介入对效率的影响来研究偿付能力与效率之间的关系;在实证研究中,引入DEA的扩展模型—RAM,因为相对于DEA,RAM能更全面地反映保险公司的相对效率,所得到的效率值具有严格单调性,而且能处理指标出现负值的情况,这对于不多的样本特别具有吸引力;在检验不同类型保险公司的效率差异时,考虑到RAM方法得到的效率值是一个序数概念而不是绝对数量,本文采用Mann-Whitney秩和方法进行检验。     

Why is Six Sigma so successful?

There can be little doubt that Motorola, General Electric, Black and Decker, Allied Signal (now Honeywell), ABB and Bombardier, have achieved impressive business performance in recent years. Their annual reports document this success. Furthermore, in several cases, the Annual Report clearly attributes this success to having followed a Six Sigma strategy. Not surprisingly, many other companies wish to learn what Six Sigma can do for them, and their first question is 'What exactly is Six Sigma?'. Unfortunately it is rather difficult, if not impossible, to define Six Sigma in one or two sentences. This paper identifies the essential elements of Six Sigma. Some are obvious, such as the extensive use of statistical techniques by employees known as Blackbelts. However, other more subtle, but very important, features of Six Sigma are concealed within the business culture of these successful companies. It is clear to those who have participated in this success, that any company embarking on Six Sigma will not succeed if it focuses on statistics whilst failing to develop a supporting culture.     

Costs of reproduction in common eiders ( Somateria mollissima ): an assessment of relationships between reproductive effort and future survival and reproduction based on observational and experimental studies

The two traditional approaches to the study of costs of reproduction, correlational and experimental, have been used in parallel in a breeding colony of common eiders ( Somateria mollissima ) and were compared in this paper. The analysis of the observational data was based on a two-strata capture-recapture model, the strata being defined on the basis of the clutch size laid by individual females in a given year. The best model according to AIC C indicated substantial variation in survival, recapture and transition rates, but overall a pattern emerged: females laying large clutches have a somewhat higher survival and much higher capture rate than females laying small clutches, and transition from large to small clutch size occurs much more frequently than the reverse transition. The analysis of the experimental data (adding/removing one egg) showed that no clear effect was found on either survival or transition rates. We conclude by suggesting (1) that condition should be included in multi-strata models in addition to reproductive effort; (2) that a specific study design for estimating the proportion of non-breeding females should be implemented, and (3) that non-breeding (a non-observable state in this study) may be influenced by previous reproduction events.     

Costs of reproduction in common eiders ( Somateria mollissima ): An assessment of relationships between reproductive effort and future survival and reproduction based on observational and experimental studies

The two traditional approaches to the study of costs of reproduction, correlational and experimental, have been used in parallel in a breeding colony of common eiders ( Somateria mollissima ) and were compared in this paper. The analysis of the observational data was based on a two-strata capture-recapture model, the strata being defined on the basis of the clutch size laid by individual females in a given year. The best model according to AIC C indicated substantial variation in survival, recapture and transition rates, but overall a pattern emerged: females laying large clutches have a somewhat higher survival and much higher capture rate than females laying small clutches, and transition from large to small clutch size occurs much more frequently than the reverse transition. The analysis of the experimental data (adding/removing one egg) showed that no clear effect was found on either survival or transition rates. We conclude by suggesting (1) that condition should be included in multi-strata models in addition to reproductive effort; (2) that a specific study design for estimating the proportion of non-breeding females should be implemented, and (3) that non-breeding (a non-observable state in this study) may be influenced by previous reproduction events.     

Checks of model adequacy for univariate time series models and their application to econometric relationships

Tests derived from time series analysis play an important role in many empirical studies. These tests are frequently applied to the residuals obtained by fitting an econometric model using some standard estimator. We focus attention here on tests developed for univariate time series models. Various approaches to testing the adequacy of such models are discussed and compared. The validity and sefulness of applying these tests to econometric residuals are then examined and some Monte Carlo evidence is reported.     

Financial spread betting

Traditional betting has two outcomes: you win or you lose. Spread betting has many more possibilities: you can win a lot or a little; you can lose or lose much, much more than you imagined. Spread betting, say its fans, brings a whole new level of uncertainty—and excitement. It has been described as the crack cocaine of gambling. Spread bets can be laid on almost any sporting or other result, but in the field of finance it is making particular inroads. David Buik , of the City spread betting company Cantor Index Ltd, explains.     

SOME MODELS FOR OVERDISPERSED BINOMIAL DATA

Various models are currently used to model overdispersed binomial data. It is not always clear which model is appropriate for a given situation. Here we examine the assumptions and discuss the problems and pitfalls of some of these models. We focus on clustered data with one level of nesting, briefly touching on more complex strata and longitudinal data. The estimation procedures are illustrated and some critical comments are made about the various models. We indicate which models are restrictive and how and which can be extended to model more complex situations. In addition some inadequacies in testing procedures are noted. Recommendations as to which models should be used, and when, are made.     

风险偏好与新农保缴费档次选择

假定参保者手中有足够缴纳新农保高档次费用的资金,选择新农保缴费档次时,其考虑的是新农保与其他资产组成的投资组合的效用。根据广东省新农保参保者的问卷调查和有序logit模型研究发现,越偏好风险的农民越情愿选择新农保较低缴费档次和按年分期缴费,而将剩余资金投资于别的风险较高的资产,寻求投资组合的效用最大化。另外,家庭资产规模越大的农民,越倾向于选择较高缴费档次和一次性缴清费用。     

In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?

It is widely known that significant in-sample evidence of predictability does not guarantee significant out-of-sample predictability. This is often interpreted as an indication that in-sample evidence is likely to be spurious and should be discounted. In this paper, we question this interpretation. Our analysis shows that neither data mining nor dynamic misspecification of the model under the null nor unmodelled structural change under the null are plausible explanations of the observed tendency of in-sample tests to reject the no-predictability null more often than out-of-sample tests. We provide an alternative explanation based on the higher power of in-sample tests of predictability in many situations. We conclude that results of in-sample tests of predictability will typically be more credible than results of out-of-sample tests.     

Some tests of whether several samples are from identical populations

We observe s Independent samples, from unknown continuous distributions. The problem is to test the hypothesis that all the distributions are identical. The distribution of the numbers of observations from s-1 of the samples which fall in cells whose Boundaries are selected order statistics of the remaining sample, the number of cells increasing gradually with the sample sizes, is investigated. It is shown that under the null hypothesis and nearDy alternatives, as the sample sizes Increase these numbers of observations can be considered to be slightly rounded off normal random variables, the amount rounded off decreasing as sample sizes increase. Using these results, various tests of the hypothesis can be constructed and analyzed.     

A Bayesian Time Series Model of Multiple Structural Changes in Level,Trend, and Variance

We investigate whether seasonal-adjustment procedures are, at least approximately, linear data transformations. This question was initially addressed by Young and is important with respect to many issues including estimation of regression models with seasonally adjusted data. We focus on the X-11 program and rely on simulation evidence, involving linear unobserved component autoregressive integrated moving average models. We define a set of properties for the adequacy of a linear approximation to a seasonal-adjustment filter. These properties are examined through statistical tests. Next, we study the effect of X-11 seasonal adjustment on regression statistics assessing the statistical significance of the relationship between economic variables. Several empirical results involving economic data are also reported.     

Embedding latent class regression and latent class distal outcome models into cluster-weighted latent class analysis: a detailed simulation experiment

Usually in latent class (LC) analysis, external predictors are taken to be cluster conditional probability predictors (LC models with external predictors), and/or score conditional probability predictors (LC regression models). In such cases, their distribution is not of interest. Class-specific distribution is of interest in the distal outcome model, when the distribution of the external variables is assumed to depend on LC membership. In this paper, we consider a more general formulation, that embeds both the LC regression and the distal outcome models, as is typically done in cluster-weighted modelling. This allows us to investigate (1) whether the distribution of the external variables differs across classes, (2) whether there are significant direct effects of the external variables on the indicators, by modelling jointly the relationship between the external and the latent variables. We show the advantages of the proposed modelling approach through a set of artificial examples, an extensive simulation study and an empirical application about psychological contracts among employees and employers in Belgium and the Netherlands.     

Adaptive truncated weighting for improving marginal structural model estimation of treatment effects informally censored by subsequent therapy

Randomized clinical trials are designed to estimate the direct effect of a treatment by randomly assigning patients to receive either treatment or control. However, in some trials, patients who discontinued their initial randomized treatment are allowed to switch to another treatment. Therefore, the direct treatment effect of interest may be confounded by subsequent treatment. Moreover, the decision on whether to initiate a second‐line treatment is typically made based on time‐dependent factors that may be affected by prior treatment history. Due to these time‐dependent confounders, traditional time‐dependent Cox models may produce biased estimators of the direct treatment effect. Marginal structural models (MSMs) have been applied to estimate causal treatment effects even in the presence of time‐dependent confounders. However, the occurrence of extremely large weights can inflate the variance of the MSM estimators. In this article, we proposed a new method for estimating weights in MSMs by adaptively truncating the longitudinal inverse probabilities. This method provides balance in the bias variance trade‐off when large weights are inevitable, without the ad hoc removal of selected observations. We conducted simulation studies to explore the performance of different methods by comparing bias, standard deviation, confidence interval coverage rates, and mean square error under various scenarios. We also applied these methods to a randomized, open‐label, phase III study of patients with nonsquamous non‐small cell lung cancer. Copyright © 2015 John Wiley & Sons, Ltd.     

Men matter more: the social class identity of married British women, 1985–1991

Summary.  We investigate the class identity of married women as it relates to their own and their husband's class position. Whereas previous workers have attempted to test whether identity depends solely on the husband's position, not at all on the husband's position or equally on the husband's and wife's position, leaving out all intermediate cases, we estimate new diagonal reference models that quantify the relative weight of each partner's class position on their own class identity. In previous literature, it was also argued that women who work full time should be more likely to adopt a sharing model than other women and in some cases these different types of women were compared. We move beyond this simple dichotomy and more systematically formulate hypotheses about the conditions under which women attach more or less weight to their own class position and less or more weight respectively to that of their husbands. To test these hypotheses, we consider models where the weights are allowed to depend on characteristics of each partner and the couple. Using the British Social Attitudes Survey data for 1985–1991, we find that, when the husband's commitment to the labour force exceeds that of the wife, the husband's weight exceeds the wife's weight but, when the wife's commitment exceeds that of the husband's, the weights are approximately equal. We also find (unexpectedly) that women who hold higher positions than their husbands attach more weight to their husband's position than to their own position.     

On weighted composite scores for early Alzheimer's trials

Recent research on finding appropriate composite endpoints for preclinical Alzheimer's disease has focused considerable effort on finding “optimized” weights in the construction of a weighted composite score. In this paper, several proposed methods are reviewed. Our results indicate no evidence that these methods will increase the power of the test statistics, and some of these weights will introduce biases to the study. Our recommendation is to focus on identifying more sensitive items from clinical practice and appropriate statistical analyses of a large Alzheimer's data set. Once a set of items has been selected, there is no evidence that adding weights will generate more sensitive composite endpoints.     

Nonparametric maximum likelihood estimation for artificially truncated absence data

In manpower planning it is cornmoniy tue case tnat employees withuraw from active service for a period of time before returning to take up post at a later date. Such periods of absence are frequently of major concern to employers who are anxious to ensure that employees return as soon as possible. The distribution of duration of such periods of absence are therefore of considerable interest as is the probability that such employees will ever return to active service. In this paper we derive a nonparametric estimator for such a lifetime distribution based on renewal data which are subject to various forms of incompleteness, namely right censoring, left and right truncation, and forward recurrence. Artificial truncation is used to ensure that the data are time homogeneous. A nonparametric maximum likelihood estimator for the lifetime.     

A Study of Statistical Aspects of the Love Canal Environmental Monitoring Study

A major study released in May 1982 by the U.S. Environmental Protection Agency (EPA), in conjunction with the U.S. Department of Health and Human Services, concluded that a residential area surrounding the Love Canal chemical waste dump site exhibited no clear evidence of Canal-related contamination. Considering EPA study design and statistical methods used in data interpretation, we have reservations regarding the conclusions drawn from the study by the EPA and others. Our reservations focus mainly on the high likelihood of achieving only low power for detecting differences in chemical prevalence between the three sampling areas identified in the study. It is our conclusion that no decision can be reached concerning habitability of this area until a more comprehensive study is completed.     

Confidence intervals for impulse responses under departures from normality

Monte Carlo evidence shows that in structural VAR models with fat-tailed or skewed innovations the coverage accuracy of impulse response confidence intervals may deterorate substantially compared to the same model with Gaussian innovations. Empirical evidance suggests that such departures from normality are quite plausible for economic time series. The simulation results suggest that applied researchers are best off using nonparametric bootstrap intervals for impulse responses, regardless of whether or not there is evidence of fat tails or skewness in the error distribution. Allowing for departures from normality is shown to considerably weaken the evidence of the delayed overshooting puzzle in Eichenbaum and Evans (1995).