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1.
Zhu Jun 《浙江大学学报(A卷英文版)》2000,1(1):78-90
New approaches based on general mixed linear models were presented for analyzing complex quantitative traits in animal models,
seed models and QTL (quantitative trait locus) mapping models. Variances and covariances can be appropriately estimated by
MINQUE (minimum norm quadratic unbiased estimation) approaches. Random genetic effects can be predicted without bias by LUP
(linear unbiased prediction) or AUP (adjusted unbiased prediction) methods. Mixed-model based composite interval mapping (MCIM)
methods are suitable for efficiently searching QTLs along the whole genome. Bayesian methods and Markov Chain Monte Carlo
(MCMC) methods can be applied in analyzing parameters of random effects as well as their variances.
Projects supported by NSFC (39670390, 39893350) and the NIH Grant GM32518 相似文献
2.
《Journal of research on educational effectiveness》2013,6(1):103-127
ABSTRACTRandomized experiments are considered the gold standard for causal inference because they can provide unbiased estimates of treatment effects for the experimental participants. However, researchers and policymakers are often interested in using a specific experiment to inform decisions about other target populations. In education research, increasing attention is being paid to the potential lack of generalizability of randomized experiments because the experimental participants may be unrepresentative of the target population of interest. This article examines whether generalization may be assisted by statistical methods that adjust for observed differences between the experimental participants and members of a target population. The methods examined include approaches that reweight the experimental data so that participants more closely resemble the target population and methods that utilize models of the outcome. Two simulation studies and one empirical analysis investigate and compare the methods’ performance. One simulation uses purely simulated data while the other utilizes data from an evaluation of a school-based dropout prevention program. Our simulations suggest that machine learning methods outperform regression-based methods when the required structural (ignorability) assumptions are satisfied. When these assumptions are violated, all of the methods examined perform poorly. Our empirical analysis uses data from a multisite experiment to assess how well results from a given site predict impacts in other sites. Using a variety of extrapolation methods, predicted effects for each site are compared to actual benchmarks. Flexible modeling approaches perform best, although linear regression is not far behind. Taken together, these results suggest that flexible modeling techniques can aid generalization while underscoring the fact that even state-of-the-art statistical techniques still rely on strong assumptions. 相似文献
3.
We evaluate the performance of the most common estimators of latent Markov (LM) models with covariates in the presence of direct effects of the covariates on the indicators of the LM model. In LM modeling it is common practice not to model such direct effects, ignoring the consequences that might have on the overall model fit and the parameters of interest. However, in the general literature about latent variable modeling it is well known that unmodeled direct effects can severely bias the parameter estimates of the model at hand. We evaluate how the presence of direct effects in?uences the bias and efficiency of the 3 most common estimators of LM models, the 1-step, 2-step, and 3-step approaches. Furthermore, we propose amendments (that were thus far not used in the context of LM modeling) to the 2- and 3-step approaches that make it possible to account for direct effects and eliminate bias as a consequence. This is done by modeling the (possible) direct effects in the first step of the stepwise estimation procedures. We evaluate the proposed estimators through an extensive simulation study, and illustrate them via a real data application. Our results show, first, that the augmented 2-step and 3-step approaches are unbiased and efficient estimators of LM models with direct effects. Second, ignoring the direct effects leads to biased estimates with all existing estimators, the 1-step approach being the most sensitive. 相似文献
4.
林希 《西安文理学院学报》2007,10(4):39-42
利用正则化的局部多项式预测法对logistic混沌映射时间序列进行预测,并分析了预测误差.结果显示正则化的局部多项式预测法对非线性时间序列具有良好的特性. 相似文献
5.
《Structural equation modeling》2013,20(4):487-513
We consider a general type of model for analyzing ordinal variables with covariate effects and 2 approaches for analyzing data for such models, the item response theory (IRT) approach and the PRELIS-LISREL (PLA) approach. We compare these 2 approaches on the basis of 2 examples, 1 involving only covariate effects directly on the ordinal variables and 1 involving covariate effects on the latent variables in addition. 相似文献
6.
通过分析线性代数课程教学内容特点、教学现状,结合教学实践证明,优化教学内容、教学方法、教学手段,注重应用能力的培养,改革考试和成绩的评定方法,是提高线性代数课程教学质量的有效途径。 相似文献
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利用分子力学和量子化学方法计算出烷基硫醇类化合物的分子结构描述参数,用多元线性回归法建立化合物在不同极性色谱柱上的QSRR模型。烷基硫醇类化合物在不同极性色谱柱上的气相色谱保留指数与其拓扑指数之间具有较好的线性关系。建立的不同极性色谱柱上的烷基硫醇类化合物的色谱保留QSRR模型预测此类化合物的色谱保留值,具有较好的稳定性和准确性。 相似文献
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Structural equation models with interaction and quadratic effects have become a standard tool for testing nonlinear hypotheses in the social sciences. Most of the current approaches assume normally distributed latent predictor variables. In this article, we describe a nonlinear structural equation mixture approach that integrates the strength of parametric approaches (specification of the nonlinear functional relationship) and the flexibility of semiparametric structural equation mixture approaches for approximating the nonnormality of latent predictor variables. In a comparative simulation study, the advantages of the proposed mixture procedure over contemporary approaches [Latent Moderated Structural Equations approach (LMS) and the extended unconstrained approach] are shown for varying degrees of skewness of the latent predictor variables. Whereas the conventional approaches show either biased parameter estimates or standard errors of the nonlinear effects, the proposed mixture approach provides unbiased estimates and standard errors. We present an empirical example from educational research. Guidelines for applications of the approaches and limitations are discussed. 相似文献
11.
本文通过分析当前数字资源评估的常用方法和一般过程,给出基于样本权重的数字资源评价指标体系构建方法,并根据层次分析法和功效系数法两种不同的评估统计模型,对同一数字资源的指标体系,给出了单一指标以及总体的定量评价。 相似文献
12.
Environmental impact prediction using remote sensing images 总被引：1，自引：0，他引：1
Pezhman ROUDGARMI Masoud MONAVARI Jahangir FEGHHI Jafar NOURI Nematollah KHORASANI 《浙江大学学报(A卷英文版)》2008,9(3):381-390
Environmental impact prediction is an important step in many environmental studies. A wide variety of methods have been developed in this concern. During this study, remote sensing images were used for environmental impact prediction in Robatkarim area, Iran, during the years of 2005-2007. It was assumed that environmental impact could be predicted using time series satellite imageries. Natural vegetation cover was chosen as a main environmental element and a case study. Environmental impacts of the regional development on natural vegetation of the area were investigated considering the changes occurred on the extent of natural vegetation cover and the amount of biomass. Vegetation data, land use and land cover classes （as activity factors） within several years were prepared using satellite images. The amount ofbiomass was measured by Soil-adjusted Vegetation Index （SAVI） and Normalized Difference Vegetation Index （NDVI） based on satellite images. The resulted biomass estimates were tested by the paired samples t-test method. No significant difference was observed between the average biomass of estimated and control samples at the 5% significance level. Finally, regression models were used for the environmental impacts prediction. All obtained regression models for prediction of impacts on natural vegetation cover show values over 0.9 for both correlation coefficient and R-squared. According to the resulted methodology, the prediction models of projects and plans impacts can also be developed for other environmental elements which may be derived using time series remote sensing images. 相似文献
13.
Keith F. Widaman Kevin J. Grimm Dawnté R. Early Richard W. Robins Rand D. Conger 《Structural equation modeling》2013,20(3):384-408
Difficulties arise in multiple-group evaluations of factorial invariance if particular manifest variables are missing completely in certain groups. Ad hoc analytic alternatives can be used in such situations (e.g., deleting manifest variables), but some common approaches, such as multiple imputation, are not viable. At least 3 solutions to this problem are viable: analyzing differing sets of variables across groups, using pattern mixture approaches, and a new method using random number generation. The latter solution, proposed in this article, is to generate pseudo-random normal deviates for all observations for manifest variables that are missing completely in a given sample and then to specify multiple-group models in a way that respects the random nature of these values. An empirical example is presented in detail comparing the 3 approaches. The proposed solution can enable quantitative comparisons at the latent variable level between groups using programs that require the same number of manifest variables in each group. 相似文献
14.
Bruce Austin Brian French Olusola Adesope Chad Gotch 《Journal of Experimental Education》2017,85(4):559-573
Measures of variability are successfully used in predictive modeling in research areas outside of education. This study examined how standard deviations can be used to address research questions not easily addressed using traditional measures such as group means based on index variables. Student survey data were obtained from the Organisation for Economic Co-operation and Development to examine standard deviation predictors in multilevel models. These predictors and interactions explained additional variation in the dependent variable beyond the control variables. Models using biased and unbiased standard deviations were compared. Meaningful differences were found between the models. Findings supported how standard deviation predictors may increase explanatory power and accuracy of models commonly used in educational research. 相似文献
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SPSS预测模型在商场中的应用 总被引：3，自引：0，他引：3
徐林 《宁波职业技术学院学报》2005,9(2):44-47
探讨了SPSS 12统计软件包中回归、指数平滑及ARIMA(自回归求和移动平均)等时间序列分析模块的建模及预测方法。根据金星商场1997年～2005年，1～12月的销售历史资料，建立对数模型、指数平滑模型和ARIMA乘积模型，并对三的预测结果进行比较分析，给出了平均相对误差。得出ARIMA乘积模型误差最小，它适于对有趋势性和周期性的观察数据进行预测。SPSS12统计软件包时间序列分析模块操作方便，在商场统计预测中有广阔的应用前景。 相似文献
17.
矿井瓦斯涌出量的遗传神经网络预测研究 总被引：1，自引：0，他引：1
矿井瓦斯涌出系统是非线性变化的复杂系统,传统的瓦斯涌出量预测方法存在一定的局限性。根据改进遗传算法（IGA）和BP算法的特点,将两者结合起来,利用改进遗传算法优化BP网络权重和阈值,形成IGA-BP混合算法,用于对矿井瓦斯涌出量进行科学预测。检验结果表明,基于IGA-BP混合算法的遗传神经网络模型可靠,预测精度高,效果良好。 相似文献
18.
ABSTRACT Maths anxiety has been of great concern for many educators and educational policymakers because of its adverse effects on students’ maths performance and career path. Various empirical studies have been conducted to explore the factors predicting maths anxiety, and they have typically been based on a limited set of pre-specified variables, such as maths performance and student self-concept. However, to fully grasp the nature of maths anxiety, an exploratory study based on more elaborate prediction models using a wider variety of variables can also benefit educators. To explore the important predictors of maths anxiety and examine the possibility of achieving an acceptable level of prediction accuracy, this study employed the random forest algorithm, logistic regression, and the hierarchical general linear model to build prediction models for maths anxiety based on 194 variables collected from PISA student questionnaires. Among the factors predicting maths anxiety, enjoying maths, self-concept, and attributions to failure were revealed as being the most significant predictors. Confidence in oneself, persistent behavioural characteristics, and pressures from parents or teachers were also selected as important predictors. Educational implications are drawn from the findings of this study, and the advantages and drawbacks of each prediction model are discussed. 相似文献
19.
Orville B. Aftreth 《Journal of Experimental Education》2013,81(4):273-281
A recursive model of composition changes the role of revision from the lexical level in the linear models to a more central notion as the process in which writing is grounded. It leads to a view of revision in which one of the goals is to see the structure of the argument more clearly. Cognitive mapping has been demonstrated to help students see the relationships in a conceptual structure. The purpose of this study was to determine whether cognitive mapping would lead to greater improvement in stories written using a word processor than the more traditional methods (brainstorming and outlining). Brainstorming and outlining were taught in the traditional manner. Cognitive mapping was taught according to the TCU Knowledge Mapping System. Two drafts of a story (before and after instruction in brainstorming, outlining, or mapping) were collected as the dependent measures. To determine the effects of organization method on story organization, ratings of the two stories were combined in an analysis of variance with repeated measures across drafts. Significant differences were found between the mapping group and the other two groups, with the organization of the mapping group stories rated higher than either the brainstorming or outlining groups. 相似文献
20.
商品销售预测是企业管理的重要环节,也是销售管理的重要内容。销售预测不仅对企业还是对商家都很重要,因此预测的方法也很多,世界各国预测方法大约有150多种,笼统地可分为定量预测和定性预测。"逻辑斯蒂方程法"是诸多定量预测方法中的一种,文章通过讨论一个关于销售预测的案例来阐述商品销售预测方面的逻辑斯蒂方程应用。 相似文献