Table to accompany Religion/Spirituality and Change in Meaning after Bereavement: Qualitative Evidence for the Meaning Making Model

This table accompanies the manuscript entitled "Religion/Spirituality and Change in Meaning after Bereavement: Qualitative Evidence for the Meaning Making Model" by Wortmann & Park (2009). The table summarizes the sample characteristics for published, qualitative studies that describe the involvement of religion/spirituality in adjustment after bereavement. Fields include author(s)'s last name, publication year, population characteristics and sample size, study design, age of the bereaved, type or cause of death, and time post-loss.

Input Aggregation in Models of Data Envelopment Analysis: A Statistical Test with an Application to Indian Manufacturing

A problem frequently encountered in Data Envelopment Analysis (DEA) is that the total number of inputs and outputs included tend to be too many relative to the sample size. One way to counter this problem is to combine several inputs (or outputs) into (meaningful) aggregate variables reducing thereby the dimension of the input (or output) vector. A direct effect of input aggregation is to reduce the number of constraints. This, in its turn, alters the optimal value of the objective function. In this paper, we show how a statistical test proposed by Banker (1993) may be applied to test the validity of a specific way of aggregating several inputs. An empirical application using data from Indian manufacturing for the year 2002-03 is included as an example of the proposed test.