scholarly journals Numerical discretization causing error variance loss and the need for inflation

Author(s):  
Richard Ménard ◽  
Sergey Skachko ◽  
Olivier Pannekoucke
2000 ◽  
Vol 16 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Claudio Barbaranelli ◽  
Gian Vittorio Caprara

Summary: The aim of the study is to assess the construct validity of two different measures of the Big Five, matching two “response modes” (phrase-questionnaire and list of adjectives) and two sources of information or raters (self-report and other ratings). Two-hundred subjects, equally divided in males and females, were administered the self-report versions of the Big Five Questionnaire (BFQ) and the Big Five Observer (BFO), a list of bipolar pairs of adjectives ( Caprara, Barbaranelli, & Borgogni, 1993 , 1994 ). Every subject was rated by six acquaintances, then aggregated by means of the same instruments used for the self-report, but worded in a third-person format. The multitrait-multimethod matrix derived from these measures was then analyzed via Structural Equation Models according to the criteria proposed by Widaman (1985) , Marsh (1989) , and Bagozzi (1994) . In particular, four different models were compared. While the global fit indexes of the models were only moderate, convergent and discriminant validities were clearly supported, and method and error variance were moderate or low.


Author(s):  
Elcilane Araújo de Freitas ◽  
Letícia Castelo Branco ◽  
Erick Oliveira do Nascimento ◽  
André Araujo ◽  
Erb Lins

2009 ◽  
Vol 31 (1) ◽  
pp. 81
Author(s):  
Takeaki Kumazawa

Classical test theory (CTT) has been widely used to estimate the reliability of measurements. Generalizability theory (G theory), an extension of CTT, is a powerful statistical procedure, particularly useful for performance testing, because it enables estimating the percentages of persons variance and multiple sources of error variance. This study focuses on a generalizability study (G study) conducted to investigate such variance components for a paper-pencil multiple-choice vocabulary test used as a diagnostic pretest. Further, a decision study (D study) was conducted to compute the generalizability coefficient (G coefficient) for absolute decisions. The results of the G and D studies indicated that 46% of the total variance was due to the items effect; further, the G coefficient for absolute decisions was low. 古典的テスト理論は尺度の信頼性を測定するため広く用いられている。古典的テスト理論の応用である一般化可能性理論(G理論)は特にパフォーマンステストにおいて有効な分析手法であり、受験者と誤差の要因となる分散成分の割合を測定することができる。本研究では診断テストとして用いられた多岐選択式語彙テストの分散成分を測定するため一般化可能性研究(G研究)を行った。さらに、決定研究(D研究)では絶対評価に用いる一般化可能性係数を算出した。G研究とD研究の結果、項目の分散成分が全体の分散の46%を占め、また信頼度指数は高くなかった。


2005 ◽  
Vol 80 (4) ◽  
pp. 1163-1192 ◽  
Author(s):  
Ranjani Krishnan ◽  
Joan L. Luft ◽  
Michael D. Shields

Performance-measure weights for incentive compensation are often determined subjectively. Determining these weights is a cognitively difficult task, and archival research shows that observed performance-measure weights are only partially consistent with the predictions of agency theory. Ittner et al. (2003) have concluded that psychology theory can help to explain such inconsistencies. In an experimental setting based on Feltham and Xie (1994), we use psychology theories of reasoning to predict distinctive patterns of similarity and difference between optimal and actual subjective performance-measure weights. The following predictions are supported. First, in contrast to a number of prior studies, most individuals' decisions are significantly influenced by the performance measures' error variance (precision) and error covariance. Second, directional errors in the use of these measurement attributes are relatively frequent, resulting in a mean underreaction to an accounting change that alters performance measurement error. Third, individuals seem insufficiently aware that a change in the accounting for one measure has spillover effects on the optimal weighting of the other measure in a two-measure incentive system. In consequence, they make performance-measure weighting decisions that are likely to result in misallocations of agent effort.


2020 ◽  
Vol 13 (1) ◽  
pp. 1
Author(s):  
Xu Xu ◽  
Xiaolei Zou

Global Positioning System (GPS) radio occultation (RO) and radiosonde (RS) observations are two major types of observations assimilated in numerical weather prediction (NWP) systems. Observation error variances are required input that determines the weightings given to observations in data assimilation. This study estimates the error variances of global GPS RO refractivity and bending angle and RS temperature and humidity observations at 521 selected RS stations using the three-cornered hat method with additional ERA-Interim reanalysis and Global Forecast System forecast data available from 1 January 2016 to 31 August 2019. The global distributions, of both RO and RS observation error variances, are analyzed in terms of vertical and latitudinal variations. Error variances of RO refractivity and bending angle and RS specific humidity in the lower troposphere, such as at 850 hPa (3.5 km impact height for the bending angle), all increase with decreasing latitude. The error variances of RO refractivity and bending angle and RS specific humidity can reach about 30 N-unit2, 3 × 10−6 rad2, and 2 (g kg−1)2, respectively. There is also a good symmetry of the error variances of both RO refractivity and bending angle with respect to the equator between the Northern and Southern Hemispheres at all vertical levels. In this study, we provide the mean error variances of refractivity and bending angle in every 5°-latitude band between the equator and 60°N, as well as every interval of 10 hPa pressure or 0.2 km impact height. The RS temperature error variance distribution differs from those of refractivity, bending angle, and humidity, which, at low latitudes, are smaller (less than 1 K2) than those in the midlatitudes (more than 3 K2). In the midlatitudes, the RS temperature error variances in North America are larger than those in East Asia and Europe, which may arise from different radiosonde types among the above three regions.


2020 ◽  
Vol 53 (2) ◽  
pp. 1108-1113
Author(s):  
Magnus Malmström ◽  
Isaac Skog ◽  
Daniel Axehill ◽  
Fredrik Gustafsson

Author(s):  
Philipp Junker ◽  
Daniel Balzani

AbstractWe present a novel approach to topology optimization based on thermodynamic extremal principles. This approach comprises three advantages: (1) it is valid for arbitrary hyperelastic material formulations while avoiding artificial procedures that were necessary in our previous approaches for topology optimization based on thermodynamic principles; (2) the important constraints of bounded relative density and total structure volume are fulfilled analytically which simplifies the numerical implementation significantly; (3) it possesses a mathematical structure that allows for a variety of numerical procedures to solve the problem of topology optimization without distinct optimization routines. We present a detailed model derivation including the chosen numerical discretization and show the validity of the approach by simulating two boundary value problems with large deformations.


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