RLH

63

65

62

64

71

68

In second trial I get this result

RLH

0.077321964

0.065412867

0.073315509

0.07220652

0.145737896

0.086991154

It make me confused what is the problem? Please help

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RLH

63

65

62

64

71

68

In second trial I get this result

RLH

0.077321964

0.065412867

0.073315509

0.07220652

0.145737896

0.086991154

It make me confused what is the problem? Please help

+1 vote

Hi Retno,

Which programs are you using for the two trials? I assume you are switching between CBC/HB and something else (perhaps HB within SSI Web, MBC, ACBC, etc.).

RLH stands for Root Likelihood, and is a measure of model fit derived from the maximum likelihood utility estimation procedure. The RLH fit statistic is a probability that is naturally bounded to the range 0 and 1, where 0 indicates that the model is perfectly non-predictive and 1 indicates that the model perfectly fits the data.

In many of our analysis packages, including the standalone CBC/HB program, the RLH is rescaled as RLH * 1000 to avoid having to store and manipulate fractional data. This practice originated when our programs were written for DOS, and decimal data was a bit of a nuisance. The "RLH" therefore ranges from 0 to 1000. (Other programs, such as CVA and ACA, implement this practice for r^2 values as well.)

Some of our newer analysis packages represent RLH on the more formally correct 0-to-1 bounded scale. It appears that your second data set uses the more formally correct scale, while the first data set uses RLH x 1000. To compare the two, you'd simply divide the first by 1000, or multiply the second by 1000.

--Aaron Hill

Which programs are you using for the two trials? I assume you are switching between CBC/HB and something else (perhaps HB within SSI Web, MBC, ACBC, etc.).

RLH stands for Root Likelihood, and is a measure of model fit derived from the maximum likelihood utility estimation procedure. The RLH fit statistic is a probability that is naturally bounded to the range 0 and 1, where 0 indicates that the model is perfectly non-predictive and 1 indicates that the model perfectly fits the data.

In many of our analysis packages, including the standalone CBC/HB program, the RLH is rescaled as RLH * 1000 to avoid having to store and manipulate fractional data. This practice originated when our programs were written for DOS, and decimal data was a bit of a nuisance. The "RLH" therefore ranges from 0 to 1000. (Other programs, such as CVA and ACA, implement this practice for r^2 values as well.)

Some of our newer analysis packages represent RLH on the more formally correct 0-to-1 bounded scale. It appears that your second data set uses the more formally correct scale, while the first data set uses RLH x 1000. To compare the two, you'd simply divide the first by 1000, or multiply the second by 1000.

--Aaron Hill

...

Chuck