@CLeslieMP @Jarmann If someone calculates something its perfectly natural and good science to know where that estimate came from.
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@migrationman
@Jarmann Thanks. Yes, of course, agree robustness good. Just a shame some have undermined the case by being rude about it. -
@CLeslieMP
@Jarmann I agree no need to be rude (pretty emotive issue nonetheless). But I wouldn't say issue here was robustness it was... -
@CLeslieMP
@Jarmann more about being kept in dark about where estimate came from. Things Brian has published today still not sufficient...
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@CLeslieMP
@Jarmann It's simple denial. Rubbish the figures, attack the messenger. Anything but address the message. -
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@FlythenestHaven@iHealthP @CLeslieMP I use binary logistic regression, ‘bottom-up’ model ie for all 259 CCS diags covering 100% admissions. -
@Jarmann@FlythenestHaven@iHealthP @CLeslieMP based on HES data, with massive differences in coding, your results are meaningless -
@bendean1979@Jarmann@FlythenestHaven@iHealthP @CLeslieMP not necessarily meaningless, but on evidence presented flawed and presumptive -
@threestain@Jarmann@FlythenestHaven@iHealthP @CLeslieMP maybe, likely meaningless more accurate perhaps
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@CLeslieMP Not agression, incredulity. Why has
@Jarmann not published this data? His dropbox file is insufficient for us to judge his methodThanks. Twitter will use this to make your timeline better. UndoUndo
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Thanks. Twitter will use this to make your timeline better. UndoUndo
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@CLeslieMP totally untrue. No aggression simply requests for clarification why was data not peer reviewed, checked and published properly?
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@GrumpyOldDoc @CLeslieMP@Jarmann I've seen some very aggressive reponses to Jarman on Twitter this morning. - 1 more reply
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.@CLeslieMP
@Jarmann sad to see those asking to see the extraordinary data behind extraordinary claims branded as aggressive discreditingThanks. Twitter will use this to make your timeline better. UndoUndo
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