There are four things to consider while making a statement of clinical significant:
1) p, - p is just one of the parameter
2) confidence interval, that is the precision of the estimate
3) beta- the power of the study
4) magnitude of absolute difference or absolute risk difference, this can only be judged by content expert, not by statistical value
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pingfoo
Nov 27, 2017
thank you Prof
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tsf
Nov 10, 2017
Simplistically, p is the probability of error in an observation due to random error. for an example, if a statistical test produces a p of 0.003, it means that the probability of error in the observed differences (between observed and true differences) is 0.3%. With a conventional p setting at 0.05, allowing an acceptable error of 5%, we will accept the observed difference as "true" difference.
There are four things to consider while making a statement of clinical significant:
1) p, - p is just one of the parameter
2) confidence interval, that is the precision of the estimate
3) beta- the power of the study
4) magnitude of absolute difference or absolute risk difference, this can only be judged by content expert, not by statistical value
thank you Prof
Simplistically, p is the probability of error in an observation due to random error. for an example, if a statistical test produces a p of 0.003, it means that the probability of error in the observed differences (between observed and true differences) is 0.3%. With a conventional p setting at 0.05, allowing an acceptable error of 5%, we will accept the observed difference as "true" difference.
a good source of detail explanation: https://www.statsdirect.com/help/basics/p_values.htm