Suchergebnisse

In the general vector autoregressive process AR(p), multivariate least square estimation (LSE)/maximum likelihood estimation (MLE) of a subset of the parameters is considered when the complementary subset is suspected to be redundant. This may be viewed as a special case of linear constraints of autoregressive parameters. We incorporate this nonsample information in the estimation process and propose preliminary test and Stein‐type estimators for the target subset of parameters. Under local alternatives their asymptotic properties are investigated and compared with those of unrestricted and restricted LSE. The dominance picture of the estimators is presented.

ABSTRACTThis paper evaluates the effectiveness of various analytical review (AR) procedures in detecting material errors in account balances. The study tested nine nonstatistical AR procedures based on common heuristic and ratio analyses and four AR procedures based on regression analysis. Simulated account balances were seeded with various magnitudes of errors and each AR procedure was used to detect the errors. It was found that the regression approaches tended to have fewer Type I and Type II errors than other AR procedures.

AbstractAsymptotic inferences about the difference, ratio or odds‐ratio of two independent proportions are very common in diverse fields. This article defines for each parameter eight conditional inference methods. These methods depend on: (1) using a chi‐squared type statistic or a z type one; (2) using the classic Yates continuity correction or the less well‐known Conover one; and (3) whether the p‐value of the test is determined by doubling the one‐tailed p‐value or by the Mantel method (asymmetrical approach). In all cases, the conclusions are: (i) the methods based on the chi‐squared statistic should not be used, as they are too liberal; (ii) for those in favor of using the criterion of doubling the p‐value, the best method is using the z statistic with Conover continuity correction; and (iii) for those in favor of the asymmetrical approach, the best method is based on the z statistic with Conover continuity correction and the Mantel p‐value.

We consider inference about the parameter that determines the distribution of the data. In frequentist inference a very important and useful idea is that data reduction to a sufficient statistic does not lose any information about this parameter. We recall two justifications for this idea in frequentist inference. We then examine the extent to which these justifications carry over to conditional frequentist inference inference, which consists of carrying out frequentist inference conditional on an ancillary statistic. This examination shows that, in the context of conditional frequentist inference, first reducing data to a sufficient statistic is not always justified, so we should first condition on an ancillary statistic. Finally, we describe two types of practically important statistical models that illustrate this finding.

This study aimed to determine the effects of age, gender, and allergen type on serum immunoglobulin E (IgE) levels in asthma (AS) and allergic rhinitis (AR) patients. Sixty AS patients, 52 AR patients, and 61 controls were enrolled in the study. Sera of participants were assessed for total IgE level and specific IgE antibody against four allergen types (animal dander, grasses, mites, and molds). The results revealed that median level of total IgE was significantly increased in AS (218.9 IU/mL; p-value < 0.001) and AR (244.3 IU/mL; p-value < 0.001) patients compared to controls (167.1 IU/mL), while, there was no significant difference between AS and AR patients (p-value = 0.270). Logistic regression analysis demonstrated that the increased level of IgE was associated with an increased risk of AS (Odds ratio = 96.93) and AR (Odds ratio = 66.37). Receiver operating characteristic (ROC) curve analysis confirmed the predictive significance of IgE in AS and AR. The estimated area under the curve (AUC) for IgE in AS was 0.889 (p-value < 0.001), and at a cut-off value of 183.7 IU/mL, the sensitivity and specificity were 86.7 and 83.6%, respectively. Almost similar figures were estimated in AR, but the AUC was slightly lower (AUC = 0.873). The IgE level was not influenced by age groups (< 16, 16 – 40, and > 40 years) in AS patients or controls, while, it showed a significantly decreased level in the age group > 40 years of AR patients compared to the corresponding lower age groups (196.3 vs. 252.2 and 264.9 IU/mL, respectively). With respect to gender, the IgE levels showed no significant differences between males and females of patients or controls. For allergen type, mites were the most encountered allergen in age groups and males and females of AS and AR patients, and there were no significant differences between age or gender groups regarding the distribution of seropositive and seronegative patients. Further, the allergen type had no significant influence on the total IgE level. In conclusion, this study indicated the predictive significance of IgE in AS and AR. This significance was not influenced by age, gender, or allergen type.