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221.
Borja Camino-Pontes Francisco Gonzalez-Lopez Gonzalo Santamaría-Gomez Antonio Javier Sutil-Jimenez Carolina Sastre-Barrios Iñigo Fernandez de Pierola Jesus M. Cortes 《Journal of Neuropsychology》2023,17(2):302-318
Clinical evidence based on real-world data (RWD) is accumulating exponentially providing larger sample sizes available, which demand novel methods to deal with the enhanced heterogeneity of the data. Here, we used RWD to assess the prediction of cognitive decline in a large heterogeneous sample of participants being enrolled with cognitive stimulation, a phenomenon that is of great interest to clinicians but that is riddled with difficulties and limitations. More precisely, from a multitude of neuropsychological Training Materials (TMs), we asked whether was possible to accurately predict an individual's cognitive decline one year after being tested. In particular, we performed longitudinal modelling of the scores obtained from 215 different tests, grouped into 29 cognitive domains, a total of 124,610 instances from 7902 participants (40% male, 46% female, 14% not indicated), each performing an average of 16 tests. Employing a machine learning approach based on ROC analysis and cross-validation techniques to overcome overfitting, we show that different TMs belonging to several cognitive domains can accurately predict cognitive decline, while other domains perform poorly, suggesting that the ability to predict decline one year later is not specific to any particular domain, but is rather widely distributed across domains. Moreover, when addressing the same problem between individuals with a common diagnosed label, we found that some domains had more accurate classification for conditions such as Parkinson's disease and Down syndrome, whereas they are less accurate for Alzheimer's disease or multiple sclerosis. Future research should combine similar approaches to ours with standard neuropsychological measurements to enhance interpretability and the possibility of generalizing across different cohorts. 相似文献
222.
Maria T. Barendse Yves Rosseel 《The British journal of mathematical and statistical psychology》2023,76(2):327-352
Pairwise maximum likelihood (PML) estimation is a promising method for multilevel models with discrete responses. Multilevel models take into account that units within a cluster tend to be more alike than units from different clusters. The pairwise likelihood is then obtained as the product of bivariate likelihoods for all within-cluster pairs of units and items. In this study, we investigate the PML estimation method with computationally intensive multilevel random intercept and random slope structural equation models (SEM) in discrete data. In pursuing this, we first reconsidered the general ‘wide format’ (WF) approach for SEM models and then extend the WF approach with random slopes. In a small simulation study we the determine accuracy and efficiency of the PML estimation method by varying the sample size (250, 500, 1000, 2000), response scales (two-point, four-point), and data-generating model (mediation model with three random slopes, factor model with one and two random slopes). Overall, results show that the PML estimation method is capable of estimating computationally intensive random intercept and random slopes multilevel models in the SEM framework with discrete data and many (six or more) latent variables with satisfactory accuracy and efficiency. However, the condition with 250 clusters combined with a two-point response scale shows more bias. 相似文献
223.
Auburn Jimenez James Joseph Balamuta Steven Andrew Culpepper 《The British journal of mathematical and statistical psychology》2023,76(3):513-538
Cognitive diagnostic models provide a framework for classifying individuals into latent proficiency classes, also known as attribute profiles. Recent research has examined the implementation of a Pólya-gamma data augmentation strategy binary response model using logistic item response functions within a Bayesian Gibbs sampling procedure. In this paper, we propose a sequential exploratory diagnostic model for ordinal response data using a logit-link parameterization at the category level and extend the Pólya-gamma data augmentation strategy to ordinal response processes. A Gibbs sampling procedure is presented for efficient Markov chain Monte Carlo (MCMC) estimation methods. We provide results from a Monte Carlo study for model performance and present an application of the model. 相似文献
224.
Zhi Wang Xueying Tang Jingchen Liu Zhiliang Ying 《The British journal of mathematical and statistical psychology》2023,76(1):211-235
Response process data collected from human–computer interactive items contain detailed information about respondents' behavioural patterns and cognitive processes. Such data are valuable sources for analysing respondents' problem-solving strategies. However, the irregular data format and the complex structure make standard statistical tools difficult to apply. This article develops a computationally efficient method for exploratory analysis of such process data. The new approach segments a lengthy individual process into a sequence of short subprocesses to achieve complexity reduction, easy clustering and meaningful interpretation. Each subprocess is considered a subtask. The segmentation is based on sequential action predictability using a parsimonious predictive model combined with the Shannon entropy. Simulation studies are conducted to assess the performance of the new method. We use a case study of PIAAC 2012 to demonstrate how exploratory analysis for process data can be carried out with the new approach. 相似文献
225.
Recently, Phillips [Am Soc Rev, 1983; 48:560–568] reported that the homicide rate increases on the third day after heavyweight championship prize fights. The present paper reports a reanalysis of Phillips's data using more sophisticated statistical techniques and examining several theoretically important variables not discussed by Phillips or his critics. Using a conservative analysis strategy, our results suggest that the increases in homicides reported by Phillips were not a methodological artifact as suggested by Baron and Reiss [Am Soc Rev 1985; 50:347–363, 372–376]. The homicide increases only occur on the first weekend or holiday after prize fights that receive the greatest publicity. 相似文献
226.
Bayesian analysis of order-statistics models for ranking data 总被引:1,自引:0,他引:1
Philip L. H. Yu 《Psychometrika》2000,65(3):281-299
In this paper, a class of probability models for ranking data, the order-statistics models, is investigated. We extend the usual normal order-statistics model into one where the underlying random variables follow a multivariate normal distribution. Bayesian approach and the Gibbs sampling technique are used for parameter estimation. In addition, methods to assess the adequacy of model fit are introduced. Robustness of the model is studied by considering a multivariate-t distribution. The proposed method is applied to analyze the presidential election data of the American Psychological Association (APA).The author is grateful to K. Lam, K.F. Lam, the Editor, an associate editor, and three reviewers for their valuable comments and suggestions. This research was substantially supported by the CRCG grant 335/017/0015 of the University of Hong Kong and a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. HKU 7169/98H). Upon completion of this paper, I became aware that similar work had been done independently by K.G. Yao and U. Böckenholt (1999). 相似文献
227.
A novel classification framework for clinical decision making that uses an Extremely Randomized Tree (ERT) based feature selection and a Diverse Intensified Strawberry Optimized Neural network (DISON) is proposed. DISON is a Feed Forward Artificial Neural Network where the optimization of weights and bias is done using a two phase training strategy. Two algorithms namely Strawberry Plant Optimization (SPO) algorithm and Gradient-descent Back-propagation algorithm are used sequentially to identify the optimum weights and bias. The novel two phase training method and the stochastic duplicate-elimination strategy of SPO helps in addressing the issue of local optima associated with conventional neural networks. The relevant attributes are selected based on the feature importance values computed using an ERT classifier.Vertebral Column, Pima Indian diabetes (PID), Cleveland Heart disease (CHD) and Statlog Heart disease (SHD) datasets from the University of California Irvine machine learning repository are used for experimentation. The framework has achieved an accuracy of 87.17% for Vertebral Column, 90.92% for PID, 93.67% for CHD and 94.5% for SHD. The classifier performance has been compared with existing works and is found to be competitive in terms of accuracy, sensitivity and specificity. Wilcoxon test confirms the statistical superiority of the proposed method. 相似文献
228.
Andrea L.B. Ford Brenna N. Rudolph Brittany Pennington Breanne J. Byiers 《Journal of applied behavior analysis》2020,53(1):572-583
Visual analysis is integral to the analysis of single-case experimental design (SCED) data. Previous studies have shown that many factors may influence the interrater agreement (IRA) of visual analysis. One factor that has received little direct attention is the impact of contextual information. In the current study, authors of recently published SCED studies were asked to make judgments regarding functional relations based on published datasets that met criteria for design quality. Respondents were randomly assigned to view graphs with or without contextual information and the degree of interrater agreement was compared. Results revealed that contextual information had no impact on IRA for decisions of a functional relation. IRA was high across both groups for 6 of the 7 datasets examined. Implications and recommendations based on these results are discussed. 相似文献
229.
AbstractExtended redundancy analysis (ERA) combines linear regression with dimension reduction to explore the directional relationships between multiple sets of predictors and outcome variables in a parsimonious manner. It aims to extract a component from each set of predictors in such a way that it accounts for the maximum variance of outcome variables. In this article, we extend ERA into the Bayesian framework, called Bayesian ERA (BERA). The advantages of BERA are threefold. First, BERA enables to make statistical inferences based on samples drawn from the joint posterior distribution of parameters obtained from a Markov chain Monte Carlo algorithm. As such, it does not necessitate any resampling method, which is on the other hand required for (frequentist’s) ordinary ERA to test the statistical significance of parameter estimates. Second, it formally incorporates relevant information obtained from previous research into analyses by specifying informative power prior distributions. Third, BERA handles missing data by implementing multiple imputation using a Markov Chain Monte Carlo algorithm, avoiding the potential bias of parameter estimates due to missing data. We assess the performance of BERA through simulation studies and apply BERA to real data regarding academic achievement. 相似文献
230.
Inês M. Tavares PhD Natalie O. Rosen PhD Julia R. Heiman PhD Pedro J. Nobre PhD 《Family process》2024,63(1):192-209
There is limited understanding of the dynamic between relational and sexual well-being as couples adjust to new parenthood, despite this being a vulnerable period for couples' relationships. This study was aimed at examining the bidirectional links between relationship quality and sexual well-being (i.e., sexual satisfaction, sexual distress) across the transition to parenthood. We assessed new parent couples (N = 257) across four time points (two prenatal) from mid-pregnancy through 6 months postpartum. Parallel dyadic latent growth curve modeling was employed to examine the associations between trajectories of perceived relationship quality, sexual satisfaction, and sexual distress. New parents' declines in relationship quality were associated with declines in own and partners' sexual satisfaction and with increases in own sexual distress. Mothers' prenatal relationship quality and sexual distress predicted subsequent changes in own sexual distress and fathers' relationship quality, respectively. Results indicate that changes to new parents' relational and sexual well-being mutually influence each other over time. Current results indicate that the impact of the transition on couples' relationships is partly determined by own and partners' prenatal factors, to which clinicians and researchers can attend to early on. Cross-domain links between relational and sexual well-being should be considered in research and clinical practice. 相似文献