On robusiness of the normal-theory based asymptotic distributions of three reliability coefficient estimates

Psychometrika ◽  
2002 ◽  
Vol 67 (2) ◽  
pp. 251-259 ◽  
Author(s):  
Ke-Hai Yuan ◽  
Peter M. Bentler
Keyword(s):  
Asymptotic Distributions ◽  
Reliability Coefficient ◽  
Coefficient Estimates ◽  
Normal Theory

scholarly journals The Equivalence of Asymptotic Distributions under Randomisation and Normal Theories

1953 ◽  
Vol 1 (3) ◽  
pp. 139-147 ◽  
Author(s):  
Samuel D. Silvey
Keyword(s):  
Asymptotic Distributions ◽  
Mathematical Statistics ◽  
Inference Problem ◽  
Normal Theory ◽  
Alternative Approaches ◽  
Distribution Of A Statistic

§ 1. Introduction. A problem of some interest in mathematical statistics is that of determining conditions under which the randomisation distribution of a statistic and its normal theory distribution are asymptotically equivalent, as these two distributions are used in alternative approaches to the same inference problem.

scholarly journals The Asymptotic Distributions of Statistics arising in Certain Non-Parametric Tests

1954 ◽  
Vol 2 (1) ◽  
pp. 47-51 ◽  
Author(s):  
Samuel D. Silvey
Keyword(s):  
Analysis Of Variance ◽  
Related Problem ◽  
Asymptotic Distributions ◽  
Linear Combinations ◽  
Normal Theory ◽  
Non Parametric

In a previous paper [5] the equivalence of randomisation and normal theory distributions of linear combinations was discussed. In the present paper we discuss the asymptotic randomisation distributions of statistics used in analysis of variance and in a closely related problem which includes, in particular, the “problem of m-rankings“. Kruskal [4] has studied the first of these questions in the case where observations are replaced by ranks.

STUDI KARAKTERISTIK SISWA SLTA DI KOTA MEDAN

2013 ◽  
Vol 6 (2) ◽  
Author(s):  
Nathanael Sitanggang ◽  
Abdul Hasan Saragih
Keyword(s):  
High School ◽  
Quantitative Method ◽  
Female Students ◽  
Senior High School ◽  
Reliability Coefficient ◽  
Male Students ◽  
Accurate Data ◽  
Male And Female ◽  
Student Characteristic

Abstrak: Tujuan penelitian ini adalah untuk mentetahui karakteristik SMA dan SMK di Medan. Karakteristik yang diteliti adalah: neuroticism, extraversion, keterbukaan, keramahan, dan hati nurani. Dengan penelitian ini kita mendapatkan data perbedaan karakter di SMA dan SMK siswa. Mendapatkan perbedaan karakter antara pria dan wanita dalam setiap kelompok sekolah. Penelitian ini di SMA dan SMK di Medan, 2008. Sampel penelitian 600 siswa. Metode Penelitian kuantitatif. Data diperoleh melalui kuesioner. Kuesioner dicoba dengan nilai koefisien reliabilitas (r=0,875). Hasil penelitian adalah: (1) Karakteristik siswa SMA (Neuroticsm, extraversion, keterbukaan, keramahan, dan hati nurani) sudah cukup dan kategori tinggi, (2) Karakteristik siswa SMK (Neuroticsm, extraversion, keterbukaan, keramahan, dan hati nurani) cukup tinggi dan kategori; (3) Para siswa perempuan SMA lebih tinggi hati nurani daripada siswa laki-laki; (4) Neuroticsm, extraversion, keterbukaan, dan keramahan antara siswa laki-laki secara signifikan tidak berbeda dengan siswa perempuan di SMA; (5) Neuroticsm, extraversion, keterbukaan, keramahan, dan conscientiousness antara mahasiswa laki-laki secara signifikan tidak berbeda dengan siswa perempuan di SMK.   Kata kunci : karakteristik siswa, SMA, SMK.   Abstract: This research was aimed to: investigate the Senior High School Studen’t Characteristic in Medan. The characteristic which investigated are: neuroticism, extraversion, openness, agreeableness, and conscientiousness. By this research we can get the accurate data that describe the differences of characters in SMA and SMK students. And then we can get the differences of characters among the male and female in each group of school. This research was taking place in SMA and SMK in Medan, 2008. The sample of this research is 600 pupils. The research was taken in the quantitative method. The data that we have got from the questioner. Questioner has been tried with the value of reliability coefficient (r=0,875). The results of the research are: (1) The SMA Studen’t Characteristic in Medan (Neuroticsm, extraversion, openness, agreeableness, and conscientiousness) is enough and high categories; (2) The SMK Student Characteristic in Medan (Neuroticsm, extraversion, openness, agreeableness, and conscientiousness) is enough and high categories; (3) The female SMA students are more conscientiousness than male students; (4) Neuroticsm, extraversion, openness, and agreeableness between male students significantly is not different with female students in SMA; (5) Neuroticsm, extraversion, openness, agreeableness, and conscientiousness between male students significantly is not different with female students in SMK. Keywords: characteristics of students, SMA, SMK

scholarly journals Understanding, Choosing, and Unifying Multilevel and Fixed Effect Approaches

2020 ◽  
pp. 1-20
Author(s):  
Chad Hazlett ◽  
Leonard Wainstein
Keyword(s):  
Random Effects ◽  
Fixed Effects ◽  
Multilevel Models ◽  
Standard Errors ◽  
Point Estimate ◽  
Fe Model ◽  
Grouped Data ◽  
Coefficient Estimates ◽  
Political Science Education ◽  
Robust Standard Errors

Abstract When working with grouped data, investigators may choose between “fixed effects” models (FE) with specialized (e.g., cluster-robust) standard errors, or “multilevel models” (MLMs) employing “random effects.” We review the claims given in published works regarding this choice, then clarify how these approaches work and compare by showing that: (i) random effects employed in MLMs are simply “regularized” fixed effects; (ii) unmodified MLMs are consequently susceptible to bias—but there is a longstanding remedy; and (iii) the “default” MLM standard errors rely on narrow assumptions that can lead to undercoverage in many settings. Our review of over 100 papers using MLM in political science, education, and sociology show that these “known” concerns have been widely ignored in practice. We describe how to debias MLM’s coefficient estimates, and provide an option to more flexibly estimate their standard errors. Most illuminating, once MLMs are adjusted in these two ways the point estimate and standard error for the target coefficient are exactly equal to those of the analogous FE model with cluster-robust standard errors. For investigators working with observational data and who are interested only in inference on the target coefficient, either approach is equally appropriate and preferable to uncorrected MLM.

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