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Statistical notes for clinical researchers: Understanding standard deviations and standard errors [PDF]
Restorative Dentistry & Endodontics, 2013 Hae-Young Kim
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Applications and Extensions of Metric Stability Analysis
Psych, 2023 Item response theory models and applications are affected by many sources of variability, including errors associated with item parameter estimation. Metric stability analysis (MSA) is one method to evaluate the effects of item parameter standard errors ...
Leah Feuerstahler
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A New Estimator for Standard Errors with Few Unbalanced Clusters
Econometrics, 2022 In linear regression analysis, the estimator of the variance of the estimator of the regression coefficients should take into account the clustered nature of the data, if present, since using the standard textbook formula will in that case lead to a ...
Gianmaria Niccodemi, Tom Wansbeek
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CESER: An R Package to Compute Cluster Estimated Standard Errors
Journal of Open Research Software, 2021 This paper presents an implementation in R of the Cluster Estimated Standard Errors (CESE) proposed by [12]. The method estimates the covariance matrix of the estimated coefficients of linear models in grouped data sets with correlation among ...
Diogo Ferrari
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ISPRS International Journal of Geo-Information, 2016 Accuracy is increasingly recognized as an important dimension in geospatial information and analyses. A strategy well suited for map users who usually have limited information about map lineages is proposed for location-specific characterization of ...
Jingxiong Zhang, Yingying Mei
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equateIRT: An R Package for IRT Test Equating
Journal of Statistical Software, 2015 The R package equateIRT implements item response theory (IRT) methods for equating different forms composed of dichotomous items. In particular, the IRT models included are the three-parameter logistic model, the two-parameter logistic model, the one ...
Michela Battauz
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Analytical Errors in End Point Biochemical Assays – Experimental Analysis and Importance [PDF]
National Journal of Laboratory Medicine, 2013 Introduction: Accurate and precise laboratory test results help immensely in the diagnosis and management of diseases. Though the analytical phase amounts to the least possible error, yet it is imperative to recognize and minimize the possible ...
Prabhat Kumar Nigam
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Classification of errors in determining trigonometry function values at standard positions
Journal of Research and Advances in Mathematics Education, 2023 One of the important materials to study in a trigonometry course is the value of trigonometric functions in standard positions. However, the results of preliminary research show that there are still many first semester students who experience errors in ...
Yayan Eryk Setiawan Setiawan, Sunardi
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Cogent Psychology, 2017 The Expectation-Maximization (EM) algorithm is a method for finding the maximum likelihood estimate of a model in the presence of missing data. Unfortunately, EM does not produce a parameter covariance matrix for standard errors.
Joshua N. Pritikin
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Variance models of the last age interval and their impact on life expectancy at subnational scales
Demographic Research, 2016 Background: The Chiang method is the most widely accepted standard for estimating life expectancy (LE) at subnational scales; it is the only method that provides an equation for the LE variance.
Ernest Lo +3 more
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