Extensions of Tests of Indirect Effect in Mediation Analysis
Chike Henry Nwankwo,
Amechi Henry Igweze
Issue:
Volume 2, Issue 1, October 2016
Pages:
1-6
Received:
19 July 2016
Accepted:
27 July 2016
Published:
5 September 2016
DOI:
10.11648/j.ijdsa.20160201.11
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Views:
Abstract: This study seeks to determine economic variables that jointly mediate upon government expenditure and unemployment in Nigeria and in proven cases of mediation, determine the type of mediation that exist. It compares the two methods of calculating indirect effect which are product of coefficient and difference of coefficients respectively. Furthermore, the study compares the three methods of testing the significance of indirect effect vis-à-vis Sobel’s test, Aroian test and Goodman’s test. The differences in these three tests are due to variations in the methods of standard error computation. This study further proposed extensions for the three variations in methods of standard error computation for a case of two mediator which may also be extended for more than two mediator cases. The results show that a combination of any two of labour force population, interest rate and inflation showed a significant evidence of partial mediation. The result of indirect effect computation shows that the method of product of coefficient gave a slightly higher result when compared to that of difference of coefficient. The proposed extension of Sobel, Aroian and Goodman tests gave the same result for all cases as their standard errors are the same. The study thus recommends employing some variable selection techniques in subsequent studies which may improve mediational results; further studies may to be carried out to seek methods of ascertaining the direction of relationship of indirect effect, other than those of the regression models; and finally studies may be carried out to determine the effect of multicolinearity on mediation results.
Abstract: This study seeks to determine economic variables that jointly mediate upon government expenditure and unemployment in Nigeria and in proven cases of mediation, determine the type of mediation that exist. It compares the two methods of calculating indirect effect which are product of coefficient and difference of coefficients respectively. Furthermo...
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Rescaling Residual Bootstrap and Wild Bootstrap
Issue:
Volume 2, Issue 1, October 2016
Pages:
7-14
Received:
20 July 2016
Accepted:
14 October 2016
Published:
28 October 2016
DOI:
10.11648/j.ijdsa.20160201.12
Downloads:
Views:
Abstract: This paper examines and discusses a comparative analysis of hypothetical data by using bootstrap methods. The residual and wild bootstrap methods, including their rescaled versions were applied on the data collected from a normal distribution with different ability levels to check whether they are significant at various assessment conditions. The wild bootstrap compared in this paper are from Mammen and Redamarche distributions. In addition their kernel density plot is used to ascertain the trends and the performance at the lower ends of the distributions for each bootstrap model and also the trend as sample size tends to infinity. To achieve this, each of the forms were represented by using at least one functional model each from hypothetical data sets of a particular bootstrap data generating process (DGP) method to illustrate how 8640 scenerios were estimated. The result shows that the Hypothetical Rescaled Residual (HRR) is found to be preferable to the Hypothetical Unrescaled Residual (HR) while Hypothetical Wild Redamarche Model (HRWR) is found to be preferable to the Hypothetical Wild Mammen model (HRWM) with reference to their bias, standard error and root mean square error (RMSE) at different levels of significance, that is, B=99, N(0,1), n1 & n3 = 10000, RMSE = -0.0004 &-0.0025 respectively. Aslo, B=99, N(0,1), n3 = 10000, RMSE = -0.0004. Even though at B=99, N(0,1), n2 = 10000, RMSE for HRWM (0.0601) is higher than HRWR (0.0595). In fact, across all the models, rescaled residual functional model out performed all other functional models considered in this paper. Also, the trends at the lower ends of the distributions for each bootstrap model shows that the empirical distributions of true distributions follow the chi-square distribution and also tends to normal distribution as sample size tends to inifinity.
Abstract: This paper examines and discusses a comparative analysis of hypothetical data by using bootstrap methods. The residual and wild bootstrap methods, including their rescaled versions were applied on the data collected from a normal distribution with different ability levels to check whether they are significant at various assessment conditions. The w...
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