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31.
Michael V. Tidwell 《Nonprofit management & leadership》2005,15(4):449-467
This study draws on social identity theory, while developing and testing the Social Identification Model of Prosocial Behavior among voluntary participants in nonprofit organizations. This model posits relationships between organization identification, commitment, satisfaction, and prosocial behavior among nonprofit volunteers. Path analysis results indicate successful identification of the model. Specifically, when volunteers identified with their nonprofit, they had higher levels of prosocial behaviors, commitment, and satisfaction. This study provides several important extensions to social identity theory and nonprofit literatures while highlighting the need for further research examining motivations behind prosocial behaviors within nonprofits. 相似文献
32.
Computing maximum likelihood estimates from type II doubly censored exponential data 总被引:1,自引:0,他引:1
Arturo J. fernández José I. Bravo Íñigo De Fuentes 《Statistical Methods and Applications》2002,11(2):187-200
It is well-known that, under Type II double censoring, the maximum likelihood (ML) estimators of the location and scale parameters, θ and δ, of a twoparameter exponential distribution are linear functions
of the order statistics. In contrast, when θ is known, theML estimator of δ does not admit a closed form expression. It is shown, however, that theML estimator of the scale parameter exists and is unique. Moreover, it has good large-sample properties. In addition, sharp
lower and upper bounds for this estimator are provided, which can serve as starting points for iterative interpolation methods
such as regula falsi. Explicit expressions for the expected Fisher information and Cramér-Rao lower bound are also derived.
In the Bayesian context, assuming an inverted gamma prior on δ, the uniqueness, boundedness and asymptotics of the highest
posterior density estimator of δ can be deduced in a similar way. Finally, an illustrative example is included. 相似文献
33.
Sets of relatively short time series arise in many situations. One aspect of their analysis may be the detection of outlying
series. We examine the performance of standard normal outlier tests applied to the means, or to simple functions of the means,
of AR(1) series, not necessarily of equal lengths. Although unequal lengths of series implies that the means have unequal
variances, that are only known approximately, it is shown that nominal significance levels hold good under most circumstances.
Thus a standard outlier test can usefully be applied, avoiding the complication of estimating the time series' parameters.
The test's power is affected by unequal lengths, being higher when the slippage occurs in one of the longer series 相似文献
34.
A finite mixture model using the multivariate t distribution has been shown as a robust extension of normal mixtures. In this paper, we present a Bayesian approach for inference about parameters of t-mixture models. The specifications of prior distributions are weakly informative to avoid causing nonintegrable posterior distributions. We present two efficient EM-type algorithms for computing the joint posterior mode with the observed data and an incomplete future vector as the sample. Markov chain Monte Carlo sampling schemes are also developed to obtain the target posterior distribution of parameters. The advantages of Bayesian approach over the maximum likelihood method are demonstrated via a set of real data. 相似文献
35.
Craig H. Mallinckrodt Christopher J. Kaiser John G. Watkin Michael J. Detke Geert Molenberghs Raymond J. Carroll 《Pharmaceutical statistics》2004,3(3):171-186
The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SEΔ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SEΔ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SEΔ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
36.
Bram Thuysbaert 《Journal of Economic Inequality》2008,6(1):33-55
Empirical applications of poverty measurement often have to deal with a stochastic weighting variable such as household size.
Within the framework of a bivariate distribution function defined over income and weight, I derive the limiting distributions
of the decomposable poverty measures and of the ordinates of stochastic dominance curves. The poverty line is allowed to depend
on the income distribution. It is shown how the results can be used to test hypotheses concerning changes in poverty. The
inference procedures are briefly illustrated using Belgian data.
An erratum to this article can be found at 相似文献
37.
Singh et al. ([13]) pointed out that the Randomized response (RR) technique proposed by Moors ([9]) is not desirable because
it fails to protect the confidentiality of the respondents and they provided two alternative strategies free from the above
drawback but limited to SRSWOR sampling only. In this paper, generalization of one of the strategies is provided for complex
survey designs, wider class of estimators and for quantitative characteristics. Relative efficiency of the modified strategy
is tested through empirical investigations.
An erratum to this article is available at . 相似文献
38.
39.
40.
Gabriela Beganu 《Statistical Methods and Applications》2007,16(3):347-356
It is known that the Henderson Method III (Biometrics 9:226–252, 1953) is of special interest for the mixed linear models
because the estimators of the variance components are unaffected by the parameters of the fixed factor (or factors). This
article deals with generalizations and minor extensions of the results obtained for the univariate linear models. A MANOVA
mixed model is presented in a convenient form and the covariance components estimators are given on finite dimensional linear
spaces. The results use both the usual parametric representations and the coordinate-free approach of Kruskal (Ann Math Statist
39:70–75, 1968) and Eaton (Ann Math Statist 41:528–538, 1970). The normal equations are generalized and it is given a necessary
and sufficient condition for the existence of quadratic unbiased estimators for covariance components in the considered model. 相似文献