Bayesian Reliability Estimation and Prediction

1992 ◽  
pp. 160-176
Author(s):  
Shelemyahu Zacks
Keyword(s):  
Reliability Estimation ◽  
Estimation And Prediction

Reliability estimation and prediction of multi-state components and coherent systems

2005 ◽  
Vol 88 (1) ◽  
pp. 93-98 ◽  
Author(s):  
Jing-An Li ◽  
Yue Wu ◽  
Kin Keung Lai ◽  
Ke Liu
Keyword(s):  
Reliability Estimation ◽  
Coherent Systems ◽  
Estimation And Prediction

scholarly journals SREPT: software reliability estimation and prediction tool

2000 ◽  
Vol 39 (1-4) ◽  
pp. 37-60 ◽  
Author(s):  
Srinivasan Ramani ◽  
Swapna S. Gokhale ◽  
Kishor S. Trivedi
Keyword(s):  
Software Reliability ◽  
Reliability Estimation ◽  
Prediction Tool ◽  
Estimation And Prediction

Managing Heterogeneity of Variance in Studies of Reliability Generalization With Alpha Coefficients

Methodology ◽  
2012 ◽  
Vol 8 (2) ◽  
pp. 71-80 ◽  
Author(s):  
Juan Botella ◽  
Manuel Suero
Keyword(s):  
Reliability Estimation ◽  
Biased Sampling ◽  
Reliability Generalization ◽  
Alpha Coefficient ◽  
Range Restriction ◽  
Sampling Schemes ◽  
Cronbach's Alpha ◽  
Heterogeneous Variances ◽  
Heterogeneity Of Variance ◽  
Meta Analyses

In Reliability Generalization (RG) meta-analyses, the importance of bearing in mind the problems of range restriction or biased sampling and their influence on reliability estimation has often been highlighted. Nevertheless, the presence of heterogeneous variances in the included studies has been diagnosed in a subjective way and has not been taken into account in later analyses. Procedures to detect the presence of a variety of sampling schemes and to manage them in the analyses are proposed. The procedures are further explained with an example, by applying them to 25 estimates of Cronbach’s alpha coefficient in the Hamilton Scale for Depression.

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