The application of the durbin-watson test to the dynamic regression model under normal and non-normal errors

Until recently, a difficulty with applying the Durbin-Watson (DW) test to the dynamic linear regression model has been the lack of appropriate critical values. Inder (1986) used a modified small-disturbance distribution (SDD) to find approximate critical values. King and Wu (1991) showed that the exact SDD of the DW statistic is equivalent to the distribution of the DW statistic from the regression with the lagged dependent variables replaced by their means. Unfortunately, these means are unknown although they could be estimated by the actual variable values. This provides a justification for using the exact critical values of the DW statistic from the regression with the lagged dependent variables treated as non-stochastic regressors. Extensive Monte Carlo experiments are reported in this paper. They show that this approach leads to reasonably accurate critical values, particularly when two lags of the dependent variable are present. Robustness to non-normality is also investigated.     

Using strategic planning to drive strategic change

This article describes a case history of strategic planning, learning and change within a major division of Dowty plc. At Dowty CASE, a telecommunications company, the management team used strategic planning as a structured learning process to generate strategic change. There are many lessons which academics and practitioners alike can learn from this case of strategic planning and change in action.     

Special Issue Introduction: Exploring the Lived Experiences of Intra-EU Mobility in an Era of Complex Economic and Political Change

This paper introduces the special issue on ‘Intra-EU mobilities in times of crisis'. Intra-EU mobility has emerged as an ambivalent phenomenon. On the one hand, EU-wide opinion polls still depict freedom of movement as the most positive aspect of European integration. On the other hand, with nationalism and xenophobia on the rise, migration and mobility are increasingly problematized and challenged. Shifting attention from the master narratives about intra-EU mobility, the aim of the special issue is to bring to the fore the lived experiences of the key actors as recounted in a period of multiple European crises which, in turn, represent the visible and mediatized manifestations of more complex and deep-seated processes of political and economic change. Here we provide a chronological periodization of intra-EU mobility trends over recent decades and how they intersect with major geopolitical events, aiming to contextualise the special issue articles which are then presented.     

China’s first priority in post-war state building: A wealthy state,or a strong army?

This analysis examined causal links in China’s defence–growth nexus in 1960–2016. The results show that better growth significantly reduces military-civilian ratio and propels military reforms. The unidirectional threshold causality from growth to defence shows that the military impact on a positive change in China’s growth is little in the long term. Conversely, the growth impact of a positive change in defence has accelerated after it reaches the threshold year in 1987. This finding explains why Chinese economy stagnated when defence was prioritised and why China has risen dramatically in the Far East after three decades of fast economic growth.     

Processes of Religious and Spiritual Influence in Adolescence: Introduction to a Special Section

This paper serves as the lead article introducing the special section of the Journal of Research on Adolescence focused on processes of religious and spiritual influence during adolescence. The purpose of the special section is to review prior theory and research on the processes by which religiosity and spirituality might influence youth outcomes, present original cutting‐edge theory and research on processes of religious and spiritual influence, and point to the most fruitful directions and methodological approaches for future work in the area. The special section is guided by eight research questions which push researchers to go beyond mere bivariate associations between religion/spirituality and youth outcomes to unpacking the processes of influence at work.     

Parameter estimation in semi-linear models using a maximal invariant likelihood function

In this paper, we consider the problem of estimation of semi-linear regression models. Using invariance arguments, Bhowmik and King [2007. Maximal invariant likelihood based testing of semi-linear models. Statist. Papers 48, 357–383] derived the probability density function of the maximal invariant statistic for the non-linear component of these models. Using this density function as a likelihood function allows us to estimate these models in a two-step process. First the non-linear component parameters are estimated by maximising the maximal invariant likelihood function. Then the non-linear component, with the parameter values replaced by estimates, is treated as a regressor and ordinary least squares is used to estimate the remaining parameters. We report the results of a simulation study conducted to compare the accuracy of this approach with full maximum likelihood and maximum profile-marginal likelihood estimation. We find maximising the maximal invariant likelihood function typically results in less biased and lower variance estimates than those from full maximum likelihood.     

Increasing the sample size at interim for a two‐sample experiment without Type I error inflation

For the case of a one‐sample experiment with known variance σ²=1, it has been shown that at interim analysis the sample size (SS) may be increased by any arbitrary amount provided: (1) The conditional power (CP) at interim is ?50% and (2) there can be no decision to decrease the SS (stop the trial early). In this paper we verify this result for the case of a two‐sample experiment with proportional SS in the treatment groups and an arbitrary common variance. Numerous authors have presented the formula for the CP at interim for a two‐sample test with equal SS in the treatment groups and an arbitrary common variance, for both the one‐ and two‐sided hypothesis tests. In this paper we derive the corresponding formula for the case of unequal, but proportional SS in the treatment groups for both one‐sided superiority and two‐sided hypothesis tests. Finally, we present an SAS macro for doing this calculation and provide a worked out hypothetical example. In discussion we note that this type of trial design trades the ability to stop early (for lack of efficacy) for the elimination of the Type I error penalty. The loss of early stopping requires that such a design employs a data monitoring committee, blinding of the sponsor to the interim calculations, and pre‐planning of how much and under what conditions to increase the SS and that this all be formally written into an interim analysis plan before the start of the study. Copyright © 2009 John Wiley & Sons, Ltd.