The Role of Faith in Christian Faith-Based Humanitarian Agencies: Constructing the Taxonomy

This article sets out to establish a taxonomy of Christian faith-based humanitarian agencies, challenging assumptions that such agencies are similarly informed by Christian theology and pursue a uniform mission. Christian principles and missionary efforts are central in the development of humanitarianism, and the agencies associated with the Christian tradition comprise a prominent and growing portion of international humanitarian agencies. Little, however, is known about how Christian faith-based agencies diverge from one another in their orientation and operations, how their theological tradition shapes their humanitarianism, and whether or how they are distinct from secular agencies. Examining the humanitarianism of Christian faith-based agencies in light of their theological roots, this article delineates three classifications of Christian faith-based agencies: Accommodative–Humanitarian, Synthesis–Humanitarian, and Evangelistic–Humanitarian agencies. The study demonstrates the importance of distinguishing not simply between faith-based and secular agencies, but among faith-based agencies themselves.     

Organizing for Public Policy Effect: Aggregate Affiliated Interests in the American States*

Recent advances in the study of organizations suggest that various environmental characteristics should affect the structural characteristics of interest groups. We explore this thesis using a data set of lobbying in the American states. We use OLS regression to determine the effect of variables to measure the concepts of societal system, political culture, lobbyist registration, and state expenditures. We find that the most important variable is the total number of state lobbying efforts. In addition, as the number of lobbying increases among the states we found that a larger proportion of lobbying has been conducted by interest groups acting on their own, instead of creating affiliated aggregates. In addition, adding more variables does not increase the explanative value of the model.     

Higher-order approximations for pitman estimators and for optimal compromise estimators

Laplace approximations for the Pitman estimators of location or scale parameters, including terms O(n^?1), are obtained. The resulting expressions involve the maximum-likelihood estimate and the derivatives of the log-likelihood function up to order 3. The results can be used to refine the approximations for the optimal compromise estimators for location parameters considered by Easton (1991). Some applications and Monte Carlo simulations are discussed.     

Practical guide to sample size calculations: non‐inferiority and equivalence trials

A sample size justification is a vital part of any trial design. However, estimating the number of participants required to give a meaningful result is not always straightforward. A number of components are required to facilitate a suitable sample size calculation. In this paper, the steps for conducting sample size calculations for non‐inferiority and equivalence trials are summarised. Practical advice and examples are provided that illustrate how to carry out the calculations by hand and using the app SampSize. Copyright © 2015 John Wiley & Sons, Ltd.     

Practical guide to sample size calculations: superiority trials

A sample size justification is a vital part of any investigation. However, estimating the number of participants required to give meaningful results is not always straightforward. A number of components are required to facilitate a suitable sample size calculation. In this paper, the steps for conducting sample size calculations for superiority trials are summarised. Practical advice and examples are provided illustrating how to carry out the calculations by hand and using the app SampSize. Copyright © 2015 John Wiley & Sons, Ltd.     

Practical guide to sample size calculations: an introduction

A sample size justification is a vital step when designing any trial. However, estimating the number of participants required to give a meaningful result is not always straightforward. A number of components are required to facilitate a suitable sample size calculation. In this paper, the general steps are summarised for conducting sample size calculations with practical advice and guidance on how to utilise the app SampSize. Copyright © 2015 John Wiley & Sons, Ltd.     

Minimum Scoring Rule Inference

Proper scoring rules are devices for encouraging honest assessment of probability distributions. Just like log‐likelihood, which is a special case, a proper scoring rule can be applied to supply an unbiased estimating equation for any statistical model, and the theory of such equations can be applied to understand the properties of the associated estimator. In this paper, we discuss some novel applications of scoring rules to parametric inference. In particular, we focus on scoring rule test statistics, and we propose suitable adjustments to allow reference to the usual asymptotic chi‐squared distribution. We further explore robustness and interval estimation properties, by both theory and simulations.