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I now repeat again my cut-and-paste from Longstop's contribution a couple of weeks ago. If you don't agree with it, discuss it, don't delete it.
 
I now repeat again my cut-and-paste from Longstop's contribution a couple of weeks ago. If you don't agree with it, discuss it, don't delete it.
    "The main point he [Kennymac] makes is quite correct, that combining experiments will tend to give a more significant result (i.e. a lower P-value) than any single experiment on its own.
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    "The point that ASchlafly makes (headed '''REPLY''', shortly after KennyMac's example) is slightly misleading. You don't choose which experiments to combine on the basis of their outcomes - you either combine all relevant experiments or none. In this case, Professor Lenski chose to combine all the experiments and present a single analysis of them. That's fine.
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:The main point he [Kennymac] makes is quite correct, that combining experiments will tend to give a more significant result (i.e. a lower P-value) than any single experiment on its own.
    "The issue of whether to weight the Z-test according to sample size is not a straightforward issue. Before Whitlock's recent paper, the consensus was that the P-value already depends on sample size so it should not be weighted according to sample size. (Basically, a high degree of significance, i.e. a low P-value, can be achieved by having either a large difference between the treatments or a large experiment or, of course, both.) Whitlock's work, based on computer simulations, is an interesting contribution but cannot be regarded as the last word on the subject because any computer simulation involves assumptions about the structure of the particular experiment simulated. I cannot imagine any editor of a scientific journal rejecting a paper because it used an unweighted Z-test rather than the weighted version (or vice-versa).
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    "The conclusion, therefore, is that while there is a quantitative difference in the level of significance obtained by weighted and unweighted Z-tests, there is undeniably a significant biological effect. ASchlafly and other contributors should not be concerned that there is anything incorrect about the biological conclusions of Professor Lenski and his students or that there was anything at all underhand about their analysis or presentation of their data." [[User:DavyJones|DavyJones]] 20:39, 31 October 2008 (EDT)
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:The point that ASchlafly makes (headed '''REPLY''', shortly after KennyMac's example) is slightly misleading. You don't choose which experiments to combine on the basis of their outcomes - you either combine all relevant experiments or none. In this case, Professor Lenski chose to combine all the experiments and present a single analysis of them. That's fine.
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:The issue of whether to weight the Z-test according to sample size is not a straightforward issue. Before Whitlock's recent paper, the consensus was that the P-value already depends on sample size so it should not be weighted according to sample size. (Basically, a high degree of significance, i.e. a low P-value, can be achieved by having either a large difference between the treatments or a large experiment or, of course, both.) Whitlock's work, based on computer simulations, is an interesting contribution but cannot be regarded as the last word on the subject because any computer simulation involves assumptions about the structure of the particular experiment simulated. I cannot imagine any editor of a scientific journal rejecting a paper because it used an unweighted Z-test rather than the weighted version (or vice-versa).
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:The conclusion, therefore, is that while there is a quantitative difference in the level of significance obtained by weighted and unweighted Z-tests, there is undeniably a significant biological effect. ASchlafly and other contributors should not be concerned that there is anything incorrect about the biological conclusions of Professor Lenski and his students or that there was anything at all underhand about their analysis or presentation of their data. [[User:DavyJones|DavyJones]] 20:39, 31 October 2008 (EDT)
    
==Referring of Scientific Papers==
 
==Referring of Scientific Papers==
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