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131.
The effects of pentobarbital and d-amphetamine were studied in pigeons responding under several concurrent fixed-ratio variable-interval and concurrent fixed-ratio fixed-interval schedules of food presentation. Drug effects were compared with different fixed ratios, fixed and variable intervals, changeover delays, and with the schedules operating singly. Doses of d-amphetamine that increased or did not affect responding under the interval schedules decreased responding under the fixed-ratio schedule, whereas doses of pentobarbital that increased responding under the fixed-ratio schedule decreased or eliminated responding under the interval schedules. These effects depended both on the schedule of food delivery and the parameters of schedules arranged concurrently. Pentobarbital increased responding under the fixed-ratio schedule with 4-minute and 10-minute interval schedules arranged concurrently, but not with 1.5-minute schedules. d-Amphetamine decreased concurrent ratio and interval responding with the 1.5-minute interval schedules, but either increased or did not affect responding with the longer intervals. Changes in the parameter of one schedule altered responding controlled by that schedule and also other concurrent performances. As a consequence, the effects of drugs on each behavior were altered.  相似文献   
132.
On each of variable-ratio 10, 40, and 80 schedules of reinforcement, when rats' lever-pressing rates were stable, the concentration of a liquid reinforcer was varied within sessions. The duration of the postreinforcement pause was an increasing function of the reinforcer concentration, this effect being more marked the higher the schedule parameter. The running rate, calculated by excluding the postreinforcement pause, was unaffected by concentration. The duration of the postreinforcement pause increased with the schedule parameter, but the proportion of the interreinforcement interval taken up by the pause decreased. Consequently, the overall response rate was an increasing function of the schedule parameter; i.e., it was inversely related to reinforcement frequency, contrary to the law of effect. The running rate, however, decreased with the reinforcement frequency, in accord with the law of effect. When 50% of reinforcements were randomly omitted, the postomission pause was shorter than the postreinforcement pause, but the running rate of responses was not affected.  相似文献   
133.
Prediction and classification are two very active areas in modern data analysis. In this paper, prediction with nonlinear optimal scaling transformations of the variables is reviewed, and extended to the use of multiple additive components, much in the spirit of statistical learning techniques that are currently popular, among other areas, in data mining. Also, a classification/clustering method is described that is particularly suitable for analyzing attribute-value data from systems biology (genomics, proteomics, and metabolomics), and which is able to detect groups of objects that have similar values on small subsets of the attributes.This article is based on the Presidential Address Jacqueline Meulman gave on July 9, 2003 at the 68th Annual Meeting of the Psychometric Society held near Cagliari, Italy on the island of Sardinia.—Editor  相似文献   
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The aim of latent variable selection in multidimensional item response theory (MIRT) models is to identify latent traits probed by test items of a multidimensional test. In this paper the expectation model selection (EMS) algorithm proposed by Jiang et al. (2015) is applied to minimize the Bayesian information criterion (BIC) for latent variable selection in MIRT models with a known number of latent traits. Under mild assumptions, we prove the numerical convergence of the EMS algorithm for model selection by minimizing the BIC of observed data in the presence of missing data. For the identification of MIRT models, we assume that the variances of all latent traits are unity and each latent trait has an item that is only related to it. Under this identifiability assumption, the convergence of the EMS algorithm for latent variable selection in the multidimensional two-parameter logistic (M2PL) models can be verified. We give an efficient implementation of the EMS for the M2PL models. Simulation studies show that the EMS outperforms the EM-based L1 regularization in terms of correctly selected latent variables and computation time. The EMS algorithm is applied to a real data set related to the Eysenck Personality Questionnaire.  相似文献   
136.
    
Methods for the treatment of item non-response in attitudinal scales and in large-scale assessments under the pairwise likelihood (PL) estimation framework and under a missing at random (MAR) mechanism are proposed. Under a full information likelihood estimation framework and MAR, ignorability of the missing data mechanism does not lead to biased estimates. However, this is not the case for pseudo-likelihood approaches such as the PL. We develop and study the performance of three strategies for incorporating missing values into confirmatory factor analysis under the PL framework, the complete-pairs (CP), the available-cases (AC) and the doubly robust (DR) approaches. The CP and AC require only a model for the observed data and standard errors are easy to compute. Doubly-robust versions of the PL estimation require a predictive model for the missing responses given the observed ones and are computationally more demanding than the AC and CP. A simulation study is used to compare the proposed methods. The proposed methods are employed to analyze the UK data on numeracy and literacy collected as part of the OECD Survey of Adult Skills.  相似文献   
137.
    
We develop factor copula models to analyse the dependence among mixed continuous and discrete responses. Factor copula models are canonical vine copulas that involve both observed and latent variables, hence they allow tail, asymmetric and nonlinear dependence. They can be explained as conditional independence models with latent variables that do not necessarily have an additive latent structure. We focus on important issues of interest to the social data analyst, such as model selection and goodness of fit. Our general methodology is demonstrated with an extensive simulation study and illustrated by reanalysing three mixed response data sets. Our studies suggest that there can be a substantial improvement over the standard factor model for mixed data and make the argument for moving to factor copula models.  相似文献   
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139.
    
Correlational studies have played a major role in building our cumulative knowledge on child development. Yet as a result, we often have difficulty making causal inferences. The concern is selection effects: When children have not been randomly assigned to conditions, pre-existing biological, psychological, or social factors may bias correlations. In this article, we draw attention to sensitivity analyses, statistical techniques for estimating the robustness or fragility of results in light of potential selection effects. We highlight the coefficient of proportionality method recently developed by Oster (2019), which does not require assumptions about the number of omitted selection variables. The coefficient of proportionality provides an indication of how large the impact of unobserved selection factors would need to be—relative to observed covariates—to nullify a result. We offer two empirical examples to demonstrate the value of this method compared with other approaches used by child development researchers.  相似文献   
140.
    
We propose a new variable interval (VI) schedule that achieves constant probability of reinforcement in time while using a bounded range of intervals. By sampling each trial duration from a uniform distribution ranging from 0 to 2 T seconds, and then applying a reinforcement rule that depends linearly on trial duration, the schedule alternates reinforced and unreinforced trials, each less than 2 T seconds, while preserving a constant hazard function.  相似文献   
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