Determining Sampling Precision
Heterogeneity and frequency of the distribution of the features affect sampling precision.
How many events do I need to count?
- 1 to 2 events per disector probe on average.
- Starting point: 100 events in 100 probes containing:
- 10 sections when using the optical disector (Optical Fractionator or Fractionator)
- 10 section pairs when using the physical disector (Physical Fractionator).
- Over-count a pilot and draw sub-samples.
- Use a sampling strategy that results in an acceptable variance.
How do I account for heterogeneity?
For distributions of non-homogeneous features (such as those found in biological tissues), the precision also depends on the fraction of the volume sampled. If one distribution is more heterogeneous than the other, you must sample a larger volume to achieve the same precision as for the more homogeneous distribution.
While you can't control the heterogeneity of the distribution, you can control the sampling. If you use Optical Fractionator, you can change two sampling parameters to affect the volume fraction (and therefore the precision): section interval and disector spacing (since it is most efficient to maximize the height of the disector).
How do I choose the parameters?
Use the existing literature
Search the published literature for previous work done in the anatomical region you want to analyze.
The probe you'd like to use may have been used in the same region under similar conditions with regards to the heterogeneity of the distribution of the features. For instance, many researchers examine cell birth in the hippocampus by using Optical Fractionator to estimate the number of newly-born neurons (e.g., Horsenpiller & Peterson, 2007).
Talk to experts
If there is no guidance in the literature, seek the help of experts in the anatomical region you are sampling and/or become familiar with the salient features of the region.
Inter-section: Is there a clump of features in the direction you are sectioning that it is imperative to sample? Make the section interval small enough to include these features no matter what the random starting section is.
Intra-section: Is the distribution of features quite heterogeneous, thus warranting a larger area fraction (closer spacing of the disectors that results in more sampling)? Use a larger area fraction if there are peaks in your data that you don’t want to miss. Using that interval is likely to be a good starting point.
If you don't have any guidance, oversample and resample
If you are really unfamiliar with the region and don’t have any guidance to estimate the disector spacing and the section interval, we recommend that you oversample and resample the region in a representative animal (Slomianka & West, 2005). Educate yourself about the region, choose a section interval and a disector spacing, then decrease the interval and spacing by a factor of 2 or 3. Stereo Investigator can resample such an oversampled data file and display graphs that compare the two sampling parameters with the range of estimates generated for those parameters (Resample Oversample ). Use this data to determine the conditions where disector and section spacing are close enough to provide sufficient precision without excessive labor.
Once you've determined the disector spacing (i.e., area sub-fraction or asf) and the section interval (i.e., section sub-fractionator or ssf ), conduct a pilot study.