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factorsinfluencingnumber of sample size
NNT estimates close to 1 andcan leadlow sample size
Study Limitations resultedThe small sample size
resultscausessmall sample size
ResultsledThe small sample size
by loss(passive) was ... causedsmall sample size
by the numbers(passive) caused bysmall sample size
Potential confounding variables ( like lower SES and education ) andinfluencedsmall sample size
by rare disease(passive) caused bysmall sample size
to 20 patients , i.e. 10 patients per group(passive) was setThe sample size
to ensure that the estimates of effect size will be reported not only with adequate power but also with appropriate precision(passive) should be setThe sample size
for a maximum relative error of 10 % and a confidence interval of 95 %(passive) was setThe sample size
to 30 participants for Group 4(passive) was arbitrarily setThe sample size
at 12 subjects for study 1(passive) was setThe sample size
Study one(passive) is designedSample size
for a maximum 10 % relative error(passive) was setThe sample size
each additional studywould ... contributeto the sample size
The statistical factors ... the value selected for , the Typeinfluencethe sample size
at 155 patients per treatment arm(passive) is setThe sample size
to 50 patients based on previous studies(passive) was setThe sample size
with 80 % power(passive) was designedSample size
The statistical factorsinfluencethe sample size
at 40 cases for each group(passive) was setThe sample size
The study(passive) was designedSample size
based on feasibility and adequacy of data(passive) was setThe sample size
The need for statistical testsinfluencedby sample size
at 18 patients(passive) was setThe sample size
of participants(passive) will be composedThe sample size
at 30 ( 15 each group(passive) was setThe sample size
to 75 employed patients based on sick(passive) was setThe sample size
power calculations for a two group continuity corrected chi - square test with a 0.05 two - sided significance level and 80 % power to detect a difference in knowledge acquisition between the two groups(passive) was set bySample size
using their resultsto setsample size
Sensitivity ... # of factorsinfluencessample size
the factorsinfluencingsample size
Factorsinfluencingsample size
# of factorsinfluencessample size
Factorsinfluencesample size
the factorswill influencesample size
the factorsinfluencesample size
the factorsinfluencethe sample size
As I mentionedresultsAs I mentioned
the problemcausethe problem
a studyWhen designinga study
in insufficient statistical power to identify weak effectsresultingin insufficient statistical power to identify weak effects
to low statistical powerleadingto low statistical power
in a large standard errormight resultin a large standard error
to a lack of statistical powerleadingto a lack of statistical power
to large confidence intervals around risk estimatesleadingto large confidence intervals around risk estimates
to insufficient power and type 2 errormay leadto insufficient power and type 2 error
to lower statistical powerleadingto lower statistical power
in differences in resultscan resultin differences in results
in conclusions with insufficient powerresultsin conclusions with insufficient power
to reduced powermay have contributedto reduced power
to the lack of differences in outcomesmay have contributedto the lack of differences in outcomes
in higher error varianceresultingin higher error variance
to reduced power to find a difference ( type IImay have contributedto reduced power to find a difference ( type II
to bias in any studycould leadto bias in any study
to a high margin of errorleadsto a high margin of error
The outcome of this study(passive) may have been influenced byThe outcome of this study
to these resultsmight contributeto these results
results(passive) caused byresults
to inaccurate resultsmay leadto inaccurate results
I error(passive) caused byI error
to a false negative error ( statistical type II errormay leadto a false negative error ( statistical type II error
problems of precision of model calibration in thecausesproblems of precision of model calibration in the
in low evidenceresultingin low evidence
some problems abovemay causesome problems above
low power to detect differencescausinglow power to detect differences
alsomight leadalso
in a poor outcomeresultingin a poor outcome
to biased resultsleadingto biased results
the results reliabilityinfluencesthe results reliability
to inconclusive resultsleadingto inconclusive results
in type II errorcould resultin type II error
in failure to detect statistical significant differencesmay have resultedin failure to detect statistical significant differences
with large number of treatment levelssettingwith large number of treatment levels
to under - estimation and result in a lack of statistical significancecan leadto under - estimation and result in a lack of statistical significance
biascould have causedbias
to biascould leadto bias
a bias(passive) caused bya bias