全文获取类型
收费全文 | 281篇 |
免费 | 2篇 |
专业分类
管理学 | 42篇 |
民族学 | 1篇 |
人口学 | 25篇 |
丛书文集 | 2篇 |
理论方法论 | 32篇 |
综合类 | 2篇 |
社会学 | 145篇 |
统计学 | 34篇 |
出版年
2022年 | 2篇 |
2020年 | 4篇 |
2019年 | 16篇 |
2018年 | 8篇 |
2017年 | 10篇 |
2016年 | 6篇 |
2015年 | 5篇 |
2014年 | 13篇 |
2013年 | 40篇 |
2012年 | 7篇 |
2011年 | 9篇 |
2010年 | 10篇 |
2009年 | 4篇 |
2008年 | 8篇 |
2007年 | 16篇 |
2006年 | 8篇 |
2005年 | 8篇 |
2004年 | 8篇 |
2003年 | 5篇 |
2002年 | 8篇 |
2001年 | 7篇 |
2000年 | 3篇 |
1999年 | 2篇 |
1998年 | 6篇 |
1997年 | 1篇 |
1995年 | 6篇 |
1994年 | 2篇 |
1993年 | 2篇 |
1992年 | 3篇 |
1991年 | 7篇 |
1990年 | 4篇 |
1989年 | 1篇 |
1988年 | 5篇 |
1987年 | 2篇 |
1986年 | 3篇 |
1985年 | 3篇 |
1984年 | 2篇 |
1983年 | 1篇 |
1982年 | 1篇 |
1981年 | 4篇 |
1980年 | 3篇 |
1979年 | 3篇 |
1978年 | 1篇 |
1977年 | 1篇 |
1975年 | 4篇 |
1974年 | 2篇 |
1973年 | 4篇 |
1968年 | 1篇 |
1966年 | 1篇 |
1963年 | 2篇 |
排序方式: 共有283条查询结果,搜索用时 0 毫秒
281.
Reference‐scaled average bioequivalence (RSABE) approaches for highly variable drugs are based on linearly scaling the bioequivalence limits according to the reference formulation within‐subject variability. RSABE methods have type I error control problems around the value where the limits change from constant to scaled. In all these methods, the probability of type I error has only one absolute maximum at this switching variability value. This allows adjusting the significance level to obtain statistically correct procedures (that is, those in which the probability of type I error remains below the nominal significance level), at the expense of some potential power loss. In this paper, we explore adjustments to the EMA and FDA regulatory RSABE approaches, and to a possible improvement of the original EMA method, designated as HoweEMA. The resulting adjusted methods are completely correct with respect to type I error probability. The power loss is generally small and tends to become irrelevant for moderately large (affordable in real studies) sample sizes. 相似文献
282.
283.
Joel L. Horowitz 《Econometrica : journal of the Econometric Society》2003,71(4):1049-1082
The block bootstrap is the best known bootstrap method for time‐series data when the analyst does not have a parametric model that reduces the data generation process to simple random sampling. However, the errors made by the block bootstrap converge to zero only slightly faster than those made by first‐order asymptotic approximations. This paper describes a bootstrap procedure for data that are generated by a Markov process or a process that can be approximated by a Markov process with sufficient accuracy. The procedure is based on estimating the Markov transition density nonparametrically. Bootstrap samples are obtained by sampling the process implied by the estimated transition density. Conditions are given under which the errors made by the Markov bootstrap converge to zero more rapidly than those made by the block bootstrap. 相似文献