Treatment‐as‐usual in effectiveness studies: What is it and does it matter?

Andrée Löfholm C, Brännström L, Olsson M, Hansson K. Treatment‐as‐usual in effectiveness studies: What is it and does it matter? A hallmark of an evidence‐based practice (EBP) is the systematic appraisal of research related to the effectiveness of interventions. This study addressed the issue of interpreting results from effectiveness studies that use treatment‐as‐usual (TAU) as a comparator. Using randomised controlled studies that evaluate the effectiveness of multisystemic therapy as an illustrative example, we show that TAU includes a wide variety of treatment alternatives. Estimated treatment effects on recidivism suggest that TAU seems to contain a greater variation in underlying risk than experimental conditions, supporting the hypothesis that the content of TAU could affect outcomes. Implications for the realisation of an EBP are discussed.     

Do maternal health problems influence child's worrying status? Evidence from the British Cohort Study

Conventional methods apply symmetric prior distributions such as a normal distribution or a Laplace distribution for regression coefficients, which may be suitable for median regression and exhibit no robustness to outliers. This work develops a quantile regression on linear panel data model without heterogeneity from a Bayesian point of view, i.e. upon a location-scale mixture representation of the asymmetric Laplace error distribution, and provides how the posterior distribution is summarized using Markov chain Monte Carlo methods. Applying this approach to the 1970 British Cohort Study (BCS) data, it finds that a different maternal health problem has different influence on child's worrying status at different quantiles. In addition, applying stochastic search variable selection for maternal health problems to the 1970 BCS data, it finds that maternal nervous breakdown, among the 25 maternal health problems, contributes most to influence the child's worrying status.     

Systematic handling of missing data in complex study designs – experiences from the Health 2000 and 2011 Surveys

We present a systematic approach to the practical and comprehensive handling of missing data motivated by our experiences of analyzing longitudinal survey data. We consider the Health 2000 and 2011 Surveys (BRIF8901) where increased non-response and non-participation from 2000 to 2011 was a major issue. The model assumptions involved in the complex sampling design, repeated measurements design, non-participation mechanisms and associations are presented graphically using methodology previously defined as a causal model with design, i.e. a functional causal model extended with the study design. This tool forces the statistician to make the study design and the missing-data mechanism explicit. Using the systematic approach, the sampling probabilities and the participation probabilities can be considered separately. This is beneficial when the performance of missing-data methods are to be compared. Using data from Health 2000 and 2011 Surveys and from national registries, it was found that multiple imputation removed almost all differences between full sample and estimated prevalences. The inverse probability weighting removed more than half and the doubly robust method 60% of the differences. These findings are encouraging since decreasing participation rates are a major problem in population surveys worldwide.     

Methods to test for equality of two normal distributions

Statistical tests for two independent samples under the assumption of normality are applied routinely by most practitioners of statistics. Likewise, presumably each introductory course in statistics treats some statistical procedures for two independent normal samples. Often, the classical two-sample model with equal variances is introduced, emphasizing that a test for equality of the expected values is a test for equality of both distributions as well, which is the actual goal. In a second step, usually the assumption of equal variances is discarded. The two-sample t test with Welch correction and the F test for equality of variances are introduced. The first test is solely treated as a test for the equality of central location, as well as the second as a test for the equality of scatter. Typically, there is no discussion if and to which extent testing for equality of the underlying normal distributions is possible, which is quite unsatisfactorily regarding the motivation and treatment of the situation with equal variances. It is the aim of this article to investigate the problem of testing for equality of two normal distributions, and to do so using knowledge and methods adequate to statistical practitioners as well as to students in an introductory statistics course. The power of the different tests discussed in the article is examined empirically. Finally, we apply the tests to several real data sets to illustrate their performance. In particular, we consider several data sets arising from intelligence tests since there is a large body of research supporting the existence of sex differences in mean scores or in variability in specific cognitive abilities.     

Factors contributing to the perpetration of workplace incivility: the importance of organizational aspects and experiencing incivility from others

In recent years a growing amount of research has been conducted in the area of workplace incivility. Whereas many studies have focused on the victims and the consequences of incivility, little attention has been paid to the perpetrators and antecedents of workplace incivility. This study aims to identify possible antecedents of workplace incivility, by investigating organizational aspects as well as the possibility that being the target of incivility from co-workers and supervisors could induce incivility. A total of 512 employees (378 women and 133 men) in the school sector in a Swedish municipality completed an online questionnaire. Overall, the results of structural equation modelling analyses showed that organizational variables were related to the perpetration of incivility. A direct relationship was found between being uncivil and organizational change, job insecurity, low social support from co-workers and high job demands. However, the strongest relationship was found between experienced incivility from co-workers and instigated incivility. This could be reflecting a climate or culture of incivility in the organization, and carry implications for future practice in interventions against workplace incivility. The results indicate the importance of focusing on the perspective of the instigator to gain knowledge about the process of workplace incivility.     

A modified combination test for the analysis of a clinical trial when a protocol amendment changed the inclusion criteria

Protocol amendments are often necessary in clinical trials. They can change the entry criteria and, therefore, the population. Simply analysing the pooled data is not acceptable. Instead, each phase should be analysed separately and a combination test such as Fisher's test should be applied to the resulting p-values. In this situation, an asymmetric decision rule is not appropriate. Therefore, we propose a modification of Bauer and Köhne's test. We compare this new test with the tests of Liptak, Fisher, Bauer/Köhne and Edgington. In case of differences in variance only or only small differences in mean, Liptak's Z-score approach is the best, and the new test keeps up with the rest and is in most cases slightly superior. In other situations, the new test and the Z-score approach are not preferable. But no big differences in populations are usually to be expected due to amendments. Then, the new method is a recommendable alternative.     

A bootstrap test for single index models

Single index models are frequently used in econometrics and biometrics. Logit and Probit models arc special cases with fixed link functions. In this paper we consider a bootstrap specification test that detects nonparametric deviations of the link function. The bootstrap is used with the aim to rind a more accurate distribution under the null than the normal approximation. We prove that the statistic and its bootstrapped version have the same asymptotic distribution. In a simulation study we show that the bootstrap is able to capture the negative bias and the skewness of the test statistic. It yields better approximations to the true critical values and consequently it has a more accurate level than the normal approximation.     

Marcinkiewicz–Zygmund and ordinary strong laws for empirical distribution functions and plug-in estimators

Both Marcinkiewicz–Zygmund strong laws of large numbers (MZ-SLLNs) and ordinary strong laws of large numbers (SLLNs) for plug-in estimators of general statistical functionals are derived. It is used that if a statistical functional is ‘sufficiently regular’, then an (MZ-)SLLN for the estimator of the unknown distribution function yields an (MZ-)SLLN for the corresponding plug-in estimator. It is in particular shown that many L-, V- and risk functionals are ‘sufficiently regular’ and that known results on the strong convergence of the empirical process of α-mixing random variables can be improved. The presented approach does not only cover some known results but also provides some new strong laws for plug-in estimators of particular statistical functionals.     

Some remarks on experimental design for estimating the expectation of a stationary random process

For estimation of the mean of a stationary random process the variance-optimal choice of the observation points (the so called experimental design) is considered. For this discrete and continuous designs are introduced, some known results of process statistics are interpreted to experimental design and a proposal for simplification of the minimization problem is offered, moreover it is proved, that for monotone decreasing eovarianee functions a design, for which the points near the ends of the observation interval are more dense than in the middle, is better than the equidistant design.     

Supplier code of conduct–state-of-the-art and customisation in the electronics industry

In the field of corporate social responsibility (CSR), one efficient way to improve the ethical behaviour of a company is the implementation of a code of conduct. When focused on suppliers, this code is referred to as the supplier code of conduct (SCoC). Specific, application-oriented research on SCoCs is rare. The main goals of the present article are to define the state-of-the-art in SCoCs and to show how this review can be used in industrial practice when defining a company-specific SCoC. This article uses the electronics industry as an example. The state-of-the-art review of the content of the SCoCs is structured in five main categories of issues: labour standards, health and safety, environment, ethics and compliance. The practical relevance of this review is demonstrated by applying it in the development of a customised SCoC for a company as a part of the company's corporate risk management activities. This review uses the content analysis of SCoCs based on the website disclosures of the Forbes Fortune 2000 (Technology Hardware & Equipment) companies; which yielded 24 SCoCs. The application was done in an action research framework with a partner company, and the results were verified with the help of a focus group consisting of 10 companies.