Approximate transformation trimmed mean methods to the test of simple linear regression slope equality

To deal with the problem of non-normality and heteroscedasticity, the current study proposes applying approximate transformation trimmed mean methods to the test of simple linear regression slope equality. The distribution-free slope estimates are first trimmed on both sides and then the test statistic t is transformed by Johnson's method for each group to correct non-normality. Lastly, an approximate test such as the James second-order test, the Welch test, or the DeShon-Alexander test, which are robust for heterogeneous variances, is applied to test the equality of regression slopes. Bootstrap methods and Monte Carlo simulation results show that the proposed methods provide protection against both unusual y values, as well as unusual x values. The new methods are valid alternatives for testing the simple linear regression slopes when heteroscedastic variances and nonnormality are present.     

经济预测中的指数平滑法

指数平滑法是回归分析和时间序列相结合的一种预测方法。华伯泉同志在《统计研究》1986年第2期中介绍了这种方法,但没有解决平滑常数和初始统计量的合理确定问题,也没有提到模型和实际数据是否适合的检验问题;并且以普通回归方程中y的预测区间代替指数平滑法中Z的预测区间,这是不合适的。本文试图解决这些问题,并研究K个观测值总和的预测区间。 -、以时间为独立变量的回归模型 设Z_(n j)表示在时间n j的观测值,考虑如下形式的模型:     

抽样调查中的比估计和相关估计法

抽样调查的目的是从样本信息估计总体总数或平均数。比估计法和线性回归估计法由于使用了与y有关的辅助变量x而提高了估计这两个指标的可靠性。 为了便于叙述,我们引进下列记号: n=样本容量;N=总体单位数; f=n/N=抽样比率;g=1/f=增加因子; x=辅助变量,例如单位的容量(亩数,居民数等); y=所研究的变量; X,(?)=总体中x的总数,及其估计;     

生态环境与平地瑶的形成及族源特征

平地瑶是瑶族的一个支系,经过瑶族先民漫长的迁徙流离,大约于唐朝中期,平地瑶先民开始定居在湘桂边界的山脚、平坝及丘岗山地等较为平坦的地方.此后历经数朝,平地瑶族源不断增多,规模不断发展壮大.而生态环境的变迁则是导致平地瑶族群的形成分布以及多元化族源特征的一个重要因素.     

Associations of the lower urinary tract symptoms with the lifestyle, prostate volume, and metabolic syndrome in the elderly males

This study aimed to evaluate the influence of the lifestyle, prostate volume (PV), and metabolic syndrome (MS) on lower urinary tract symptoms (LUTS) in the elderly males. A total of 764 men aged greater than 40 years were enrolled. Their severities of LUTS were assessed by the International Prostate Symptom Score questionnaire, while their MS was diagnosed according to the criteria developed by the National Cholesterol Education Program Adult Treatment Panel III. Lifestyle factors, PV, and components of MS were compared between no/mild and moderate/severe LUTS groups. In univariate analysis, age, cigarette smoking, alcohol consumption, physical activity, and PV significantly correlated with the severity of LUTS, but the presence or any components of MS did not. Results of multivariate analysis showed that aging, cigarette smoking, lack of regular exercise, and larger PV were independent predictors for moderate/severe LUTS. Notably, the risk factors for LUTS was influenced by the presence of MS. PV may play a role in determining the severity of LUTS for men without MS, while physical activity was the critical factor for men with MS. It was suggested that healthy lifestyle would be beneficial to lessen the severity of LUTS in the elderly males.     

Improved Robust Test Statistic Based on Trimmed Means and Hall's Transformation for Two-way ANOVA Models Under Non-normality

For the two-way fixed effects ANOVA, under assumption violations, the present study employs trimmed means and Hall's transformation to correct asymmetry, and an approximate test, such as the Alexander-Govern or Welch-James test, to correct heterogeneity. The unweighted as well as weighted means analyses of omnibus effects in unbalanced designs were considered. A simulated data set was presented and computer simulations were performed to investigate the small-sample properties of the methods. The simulation results show that the proposed technique is valid and powerful compared with the conventional methods.     

Normalized Johnson's transformation one-sample trimmed t for non-normality

The present study suggests the use of the normalized Johnson transformation trimmed t statistic in the one-sample case when the assumption of normality is violated. The performance of the proposed method was evaluated by Monte Carlo simulation, and was compared with the conventional Student t statistic, the trimmed t statistic and the normalized Johnson's transformation untrimmed t statistic respectively. The simulated results indicate that the proposed method can control type I error very well and that its power is greater than the other competitors for various conditions of non-normality. The method can be easily computer programmed and provides an alternative for the conventional t test.     

Johnson's transformation two-sample trimmed t and its bootstrap method for heterogeneity and non-normality

The present study investigates the performance of Johnson's transformation trimmed t statistic, Welch's t test, Yuen's trimmed t , Johnson's transformation untrimmed t test, and the corresponding bootstrap methods for the two-sample case with small/unequal sample sizes when the distribution is non-normal and variances are heterogeneous. The Monte Carlo simulation is conducted in two-sided as well as one-sided tests. When the variance is proportional to the sample size, Yuen's trimmed t is as good as Johnson's transformation trimmed t . However, when the variance is disproportional to the sample size, the bootstrap Yuen's trimmed t and the bootstrap Johnson's transformation trimmed t are recommended in one-sided tests. For two-sided tests, Johnson's transformation trimmed t is not only valid but also powerful in comparison to the bootstrap methods.     

Testing methods for the one-way fixed effects ANOVA models of log-normal samples

For one-way fixed effects of log-normal data with unequal variance, the present study proposes a method to deal with heterogeneity. An appropriate hypothesis testing is demonstrated; and one of the approximate tests, such as the Alexander-Govern test, Welch test or James second-order test, is applied to control Type I error rate. Monte Carlo simulation is used to investigate the performance of the F test for log-scale, the F test for original scale, the James second-order test, the Welch test, and the Alexander-Govern test. The simulated results and real data analysis show that the proposed method is valid and powerful.