Changes

==Sample size calculation==

==Sample size calculation==

As mentioned earlier, it is important in any study not only that bias is minimised, but that the sample has sufficient [[Random variation#Precision|precision]] and [[Random variation#Hypothesis testing and study power|power]] (in the case of analytic studies) to answer the question(s) for which the study is intended. Both of these are closely related to the [[Random variation|random variability]] in any sample taken from a population. Although this can be reduced by increasing the sample size, a number of other considerations (usually logistical and economic considerations) will also be acting in order to reduce the number of samples which can realistically be taken. Statistical techniques are therefore available in order to calculate the required sample size. Counterintuitively, these require assumptions to be made regarding the final results of the study, as well as information regarding the required [[Random variation#Confidence intervals|level of confidence]], precision or power of the study.

As mentioned earlier, it is important in any study not only that bias is minimised, but that the sample has sufficient [[Random variation#Precision|precision]] and [[Random variation#Hypothesis testing and study power|power]] (in the case of analytic studies) to answer the question(s) for which the study is intended. Both of these are closely related to the random variability in any sample taken from a population. Although this can be reduced by increasing the sample size, a number of other considerations (usually logistical and economic considerations) will also be acting in order to reduce the number of samples which can realistically be taken. Statistical techniques are therefore available in order to calculate the required sample size. Counterintuitively, these require assumptions to be made regarding the final results of the study, as well as information regarding the required [[Random variation#Confidence intervals|level of confidence]], precision or power of the study. Sample size formulae are not given here, but can be found in most statistical textbooks.

===Expected variation in the data===

===Expected variation in the data===

===Required precision===

===Required precision===

In the case of descriptive studies, this relates to the width of the 95% confidence interval. For example, you may want to estimate the seroprevalence to Bluetongue virus to within ±10% of the true population seroprevalence, or you may want to estimate the mean skin thickness of a group of cattle following tuberculin testing to within ±1mm of the true population mean. The concept of precision is also used in analytic studies, in the form of the minimum difference between groups which you wish to detect. As this is closely associated with power calculations, it is covered in the 'power' section below.

In the case of descriptive studies, this relates to the width of the 95% confidence interval. For example, you may want to estimate the seroprevalence to Bluetongue virus to within ±10% of the true population seroprevalence, or you may want to estimate the mean skin thickness of a group of cattle following tuberculin testing to within ±1mm of the true population mean. The concept of precision is also used in analytic studies, in the form of the difference between groups which you wish to detect. As this is closely associated with power calculations, it is mentioned in the 'power' section below.

===Level of confidence===

===Level of confidence===

 

===Power===

===Power===

[[Category:Veterinary Epidemiology - Introduction|F]]

[[Category:Veterinary Epidemiology - Introduction|F]]