Association between the BDNF Val66Met polymorphism and BMI in Mexican children
Association between the BDNF Val66Met polymorphism and BMI in Mexican children
[version 1; not peer reviewed]No competing interests were disclosed
The email address should be the one you originally registered with F1000.
You registered with F1000 via Google, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Google account password, please click here.
You registered with F1000 via Facebook, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Facebook account password, please click here.
If your email address is registered with us, we will email you instructions to reset your password.
If you think you should have received this email but it has not arrived, please check your spam filters and/or contact for further assistance.
All commenters must hold a formal affiliation as per our Policies. The information that you give us will be displayed next to your comment.
User comments must be in English, comprehensible and relevant to the article under discussion. We reserve the right to remove any comments that we consider to be inappropriate, offensive or otherwise in breach of the User Comment Terms and Conditions. Commenters must not use a comment for personal attacks. When criticisms of the article are based on unpublished data, the data should be made available.
Confidence intervals estimate the degree of precision for the magnitude of the association, they do not report a measure's statistical significance, and that precision can be set to any arbitrary value such as 90%, 95% or 99%. In fact, to interpret an OR that spans the null value as indicating evidence of lack of association (or null results), is not only inappropriate but absurd as it only points to the interval in which the population parameter is estimated to be located.
Again, your belief is an example of all-or-nothing thinking, where a 95% CI that avoids the null value is considered a badge of truth (“consensus” cut-off), mistakenly considering it as a line that separates real results from false ones without scientific reasoning. That is an ideological dichotomy that is against to the intention of the original developers of the methodology, who intended that an index of the weight of evidence should be produced rather than a yes-no decision. For example, if you calculate the CI 92.84% instead of 95% now the lower and upper limits are 1.01 – 45.54, meaning that there is a 92.84% confidence that the true odds ratio would be likely to lie in that range (avoiding the imaginary “basic statistical theory behind OR”). A difference of 2.16% does not represent a much better confidence, and if a 95% CI is only used to accept/discard biological data without scientific judgment (as commonly applied to p < 0.05), it does promote lazy thinking and CI-hacking.
Finally, pretending to classify people by "understanding-or-not-understanding" based on incorrect beliefs besides showing scientific illiteracy, it's patronizing and does not belong to any real academic exchange... I hope that you avoid that pretension if you have further comments!
Confidence intervals estimate the degree of precision for the magnitude of the association, they do not report a measure's statistical significance, and that precision can be set to any arbitrary value such as 90%, 95% or 99%. In fact, to interpret an OR that spans the null value as indicating evidence of lack of association (or null results), is not only inappropriate but absurd as it only points to the interval in which the population parameter is estimated to be located.
Again, your belief is an example of all-or-nothing thinking, where a 95% CI that avoids the null value is considered a badge of truth (“consensus” cut-off), mistakenly considering it as a line that separates real results from false ones without scientific reasoning. That is an ideological dichotomy that is against to the intention of the original developers of the methodology, who intended that an index of the weight of evidence should be produced rather than a yes-no decision. For example, if you calculate the CI 92.84% instead of 95% now the lower and upper limits are 1.01 – 45.54, meaning that there is a 92.84% confidence that the true odds ratio would be likely to lie in that range (avoiding the imaginary “basic statistical theory behind OR”). A difference of 2.16% does not represent a much better confidence, and if a 95% CI is only used to accept/discard biological data without scientific judgment (as commonly applied to p < 0.05), it does promote lazy thinking and CI-hacking.
Finally, pretending to classify people by "understanding-or-not-understanding" based on incorrect beliefs besides showing scientific illiteracy, it's patronizing and does not belong to any real academic exchange... I hope that you avoid that pretension if you have further comments! READ LESS
To assess the possible association between our variables we employed chi-square test. As clearly shown, all chi-square tests are statistically signifiant, showing an association between nutritional status and genotypes(p=0.042)/alleles(p=0.037) with less than 5% chance of being do to chance. This was our final statement.
In addition, odds ratio were used to measure the magnitud of this statistically significant association. The results shows that Met homozygotes are 7 times more likely to be classified in the obesity group.
Eventhough we did not stablished neither commited to any p-value cut-off to assign stastistical significance, and given the biomedical significance of this result, we could also have stated that this likelihood (or approximation of the relative risk) is statistically significant with a 93% confidence or a 7% error (instead of the 5% given by a p=0.05 value).
Best,
Darío Martínez
To assess the possible association between our variables we employed chi-square test. As clearly shown, all chi-square tests are statistically signifiant, showing an association between nutritional status and genotypes(p=0.042)/alleles(p=0.037) with less than 5% chance of being do to chance.... READ MORE
To assess the possible association between our variables we employed chi-square test. As clearly shown, all chi-square tests are statistically signifiant, showing an association between nutritional status and genotypes(p=0.042)/alleles(p=0.037) with less than 5% chance of being do to chance. This was our final statement.
In addition, odds ratio were used to measure the magnitud of this statistically significant association. The results shows that Met homozygotes are 7 times more likely to be classified in the obesity group.
Eventhough we did not stablished neither commited to any p-value cut-off to assign stastistical significance, and given the biomedical significance of this result, we could also have stated that this likelihood (or approximation of the relative risk) is statistically significant with a 93% confidence or a 7% error (instead of the 5% given by a p=0.05 value).
Best,
Darío Martínez
Best,
Randolph Schilke
Best,
Randolph Schilke
Use of this website is subject to the F1000 Research Limited (F1000) General Terms and Conditions.
Submission of user comments to this website is subject to additional Terms and Conditions. By clicking "I accept the User Comment Terms and Conditions" before you submit your first comment, you agree to be bound by these conditions every time you submit a comment.
Terms relating to user comments