共查询到20条相似文献，搜索用时 93 毫秒
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讨论了在不完全数据下的响应变量的估计精度,当不可忽略缺失下,样本的响应有缺失数据时,其联合分布是不可识别的.现证明了估计的精度与工具变量的相关性,当工具变量独立于目标变量时,目标变量估计的方差趋于无穷大. 相似文献
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通过惩罚估计方程,对响应变量随机缺失下的线性回归模型,给出了一个变量选择方法,并结合局部二次逼近,得到了一个迭代算法,证明了此变量选择方法是相合的并且所得估计达到最优的参数收敛速度,最后通过数据模拟研究了此方法的有限样本性质. 相似文献
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王勤 《金华职业技术学院学报》2004,4(2):48-50,52
研究了相关情况下第i个顺序统计量及其标准化变量的期望、方差、协方差以及在各阶矩上的变换作用，将Gauss—Markov定理推广至一般相关的不完全样本的情形，并用最小二乘法对顺序统计量的参数作出了最佳线性无偏估计，推导出在样本值之间不相关或相关条件下计算估计量方差的公式。 相似文献
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本文研究线性回归模型中响应变量受到另一随机变量序列污染时,模型参数和污染系数的估计问题.利用贝叶斯统计原理,给出了污染系数的贝叶斯区间估计及模型参数估计. 相似文献
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文章研究因变量缺失下的线性回归模型,借助单点插补方法,首先给出模型的估计.研究参数估计量的渐近正态性,其次,对于模型系数的线性约束检验问题,基于wald方法构造检验统计量并给出其渐近分布.最后.通过数值模拟验证所提方法的有效性. 相似文献
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曹晓华 《赤峰学院学报(自然科学版)》2012,(7):4-6
本文在随机缺失的机制下,考虑了响应变量存在缺失时的非参数回归模型的统计推断,在回归函数m（x）在给定x=x0∈RP下均值的θ似然估计,并证明了该估计的渐进性,结合这个结果,给出了其渐进置信域. 相似文献
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本文讨论了生长曲线模型中共同均值参数的估计问题;在二次损失下得到了均值参数的线性估计在线性估计类中的泛容许性特征. 相似文献
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《南阳师范学院学报》2016,(12):12-17
为探究信噪比大小对非参数回归模型拟合的影响,本文针对固定设计下的非参数回归模型进行Monte Carlo数值模拟.在模拟中使用了三次B-样条估计方法,并利用AIC和BIC准则自动选择结点.结果表明:信噪比越大,均值函数估计的平均平方误差的平方根的均值和标准差越小,另外,响应变量的拟合的均方误差和平均绝对误差也越小. 相似文献
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研究者在设计测量方案时,不仅仅要考虑与所研究的问题有关联的变量,也要考虑到出现高比例无回答的可能性,要设计与缺失机制相关的变量。对于处理无回答的技术而言,多重插补是目前相对较优的方法。本文运用全国概率抽样调查数据,针对政治学敏感问题的无回答处理技术进行了探讨,介绍了多重插补的使用方法,并指出了认知、兴趣和担忧这三种变量对政治学敏感问题进行插补的功效与意义。 相似文献
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Therese D. Pigott 《Educational Research and Evaluation》2013,19(4):353-383
This paper reviews methods for handling missing data in a research study. Many researchers use ad hoc methods such as complete case analysis, available case analysis (pairwise deletion), or single-value imputation. Though these methods are easily implemented, they require assumptions about the data that rarely hold in practice. Model-based methods such as maximum likelihood using the EM algorithm and multiple imputation hold more promise for dealing with difficulties caused by missing data. While model-based methods require specialized computer programs and assumptions about the nature of the missing data, these methods are appropriate for a wider range of situations than the more commonly used ad hoc methods. The paper provides an illustration of the methods using data from an intervention study designed to increase students’ ability to control their asthma symptoms. 相似文献
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Sandip Sinharay 《Educational Measurement》2021,40(1):79-91
Technical difficulties occasionally lead to missing item scores and hence to incomplete data on computerized tests. It is not straightforward to report scores to the examinees whose data are incomplete due to technical difficulties. Such reporting essentially involves imputation of missing scores. In this paper, a simulation study based on data from three educational tests is used to compare the performances of six approaches for imputation of missing scores. One of the approaches, based on data mining, is the first application of its kind to the problem of imputation of missing data. The approach based on data mining and a multiple imputation approach based on chained equations led to the most accurate imputation of missing scores, and hence to most accurate score reporting. A simple approach based on linear regression performed the next best overall. Several recommendations are made regarding the reporting of scores to examinees with incomplete data. 相似文献
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在无人驾驶领域,依靠数据+算法支撑的智能系统将全权替代人类驾驶行为,无人驾驶汽车也因此具备高度"自主性"。其所引发交通事故侵权致损时,至少在责任主体认定、二元归责原则适用和责任类型划分等方面给现行侵权法提出挑战。而赋予无人驾驶汽车独立法律人格既与法理不符,也难应对司法实践。故我国侵权法宜通过确立三元归责原则体系(过错+无过错+公平责任),建构"产品责任+机动车交通事故责任"相结合的适用规则,并以建立无人驾驶汽车责任强制保险为配套机制的进路加以应对。 相似文献
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关于销售者的产品责任归责原则我国学者一直存在争议。我国关于销售者产品责任归责原则的相关规定存在着不明确、不符合法律逻辑的情况。从销售者承担的义务、销售者的地位、我国经济发展水平等方面考查,销售者承担无过错责任具有不合理性。销售者承担过错责任才更符合公平合理原则。 相似文献
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Holmes Finch 《教育实用测度》2013,26(4):281-301
Methods of uniform differential item functioning (DIF) detection have been extensively studied in the complete data case. However, less work has been done examining the performance of these methods when missing item responses are present. Research that has been done in this regard appears to indicate that treating missing item responses as incorrect can lead to inflated Type I error rates (false detection of DIF). The current study builds on this prior research by investigating the utility of multiple imputation methods for missing item responses, in conjunction with standard DIF detection techniques. Results of the study support the use of multiple imputation for dealing with missing item responses. The article concludes with a discussion of these results for multiple imputation in conjunction with other research findings supporting its use in the context of item parameter estimation with missing data. 相似文献
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A procedure for evaluating candidate auxiliary variable correlations with response variables in incomplete data sets is outlined. The method provides point and interval estimates of the outcome-residual correlations with potentially useful auxiliaries, and of the bivariate correlations of outcome(s) with the latter variables. Auxiliary variables found in this way can enhance considerably the plausibility of the popular missing at random (MAR) assumption if included in ensuing maximum likelihood analyses, or can alternatively be incorporated in imputation models for subsequent multiple imputation analyses. The approach can be particularly helpful in empirical settings where violations of the MAR assumption are suspected, as is the case in many longitudinal studies, and is illustrated with data from cognitive aging research. 相似文献
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Although structural equation modeling software packages use maximum likelihood estimation by default, there are situations where one might prefer to use multiple imputation to handle missing data rather than maximum likelihood estimation (e.g., when incorporating auxiliary variables). The selection of variables is one of the nuances associated with implementing multiple imputation, because the imputer must take special care to preserve any associations or special features of the data that will be modeled in the subsequent analysis. For example, this article deals with multiple group models that are commonly used to examine moderation effects in psychology and the behavioral sciences. Special care must be exercised when using multiple imputation with multiple group models, as failing to preserve the interactive effects during the imputation phase can produce biased parameter estimates in the subsequent analysis phase, even when the data are missing completely at random or missing at random. This study investigates two imputation strategies that have been proposed in the literature, product term imputation and separate group imputation. A series of simulation studies shows that separate group imputation adequately preserves the multiple group data structure and produces accurate parameter estimates. 相似文献
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Recent changes to federal guidelines for the collection of data on race and ethnicity allow respondents to select multiple race categories. Redefining race subgroups in this manner poses problems for research spanning both sets of definitions. NAEP long-term trends have used the single-race subgroup definitions for over thirty years. Little is known about the effects of redefining race subgroups on these trends. Bridging methods for reconciling the single and multiple race definitions have been developed. These methods treat single-race subgroup membership as unknown or missing. A simulation study was conducted to determine the effectiveness of four bridging methods: multiple imputation logistic regression, multiple imputation probabilistic whole assignment, deterministic whole assignment—smallest group, and deterministic whole assignment—largest group. Only the first of these methods incorporates covariate information about examinees into the bridging procedure. The other three methods only use information contained in the race item response. The simulation took into account the percentage of biracial examinees and the missing data mechanism. Results indicated that the multiple imputation logistic regression was often the best performing method. Given that all K-12 and higher education institutions will be required to use the multiple-race definitions by 2009, implications for No Child Left Behind and other federally mandated reporting are discussed. 相似文献
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BackgroundVerbal abuse during pregnancy has a greater impact than physical and sexual violence on the incidence of postnatal depression and maternal abuse behavior towards their children. In addition, exposure of children (aged 12 months to adolescence) to verbal abuse from their parents exerts an adverse impact to the children’s auditory function. However, the effect of verbal abuse during pregnancy on fetal auditory function has not yet been thoroughly investigated.ObjectiveThe objective of the study was to examine the relationship between intimate partner verbal abuse during pregnancy and newborn hearing screening (NHS) referral, which indicates immature or impaired auditory function.Participants and settingThe Japan Environment and Children’s Study is an ongoing nationwide population-based birth-cohort study designed to determine environmental factors during and after pregnancy that affect the development, health, or wellbeing of children. Pregnant women living in 15 areas of Japan were recruited between January 2011 and March 2014.MethodsMultiple imputation for missing data was performed, followed by multiple logistic regression using 16 confounding variables.ResultsOf 104,102 records in the dataset, 79,985 mother–infant pairs submitted complete data for questions related to verbal and physical abuse and the results of NHS. Of 79,985 pregnant women, 10,786 (13.5%) experienced verbal abuse and 978 (1.2%) experienced physical abuse. Of 79,985 newborns, 787 (0.98%) received a NHS referral. Verbal abuse was significantly associated with NHS referral (adjusted odds ratio: 1.44; 95% confidence interval: 1.05–1.98).ConclusionsVerbal abuse should be avoided during pregnancy to preserve the newborn’s auditory function. 相似文献
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W. Holmes Finch 《Journal of Experimental Education》2016,84(2):356-372
Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in the context of a MANOVA, with the typical default for dealing with missing data: listwise deletion. When data are missing at random, the new methods maintained the nominal Type I error rate and had power comparable to the complete data condition. When 40% of the data were missing completely at random, the Type I error rates for the new methods were inflated, but not for lower percents. 相似文献