Quantitative Parasitology 3.0

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This parasitology software provides statistically correct ways to analyse the highly aggregated (right-skewed) frequency distributions exhibited by parasites. QP3.0 is recommended to describe parasitic infections within a sample of hosts and to compare parasitic infections across different samples of hosts.

QP3.0 is free for distribution and use in education and science. When using it for academic purposes please cite:

Reiczigel J, Rózsa L 2005. Quantitative Parasitology 3.0. Budapest.  Distributed by the authors.

Alternatively, you can consult and cite the paper that introduced this software:

Rózsa L, Reiczigel J, Majoros G 2000. Quantifying parasites in samples of hosts. Journal of Parasitology, 86, 228-232.

Note that a some of the methods incorporated in  QP3.0 were either newly introduced or reconsidered in more recent articles listed below.

How to run

Runs under Windows. After download, unzip the file and find a folder named 'QP30'. Within this folder, just run the file "_qp30.exe". Do not remove the files from the folder. In VISTA, however, use the right button and then select "run as administrator". No Mac version is available.

Statistical tools available in QP3.0

1. To describe parasitic infection of a single sample of hosts:

• Descriptive statistics (N hosts, prevalence, mean & median intensity, variance/mean),

• Alternatives to calculate an exact confidence interval for the prevalence

∙ Clopper - Pearson method (this is more traditional),

∙ Sterne or Wald method (this is more advanced, see Reiczigel 2003),

• Bootstrap (BCa) confidence interval for the mean intensity,

• Exact confidence interval for the median intensity,

• Bootstrap (BCa) confidence interval for the mean abundance,

• Bootstrap (BCa) confidence interval for the mean crowding (see Reiczigel et al. 2005a),

• Aggregation indices (variance/mean, index of discrepancy, and k of the negative binomial),

2. To compare parasitic infections between two samples of hosts:

• Descriptive statistics (N hosts, prevalence, mean & median intensity, variance/mean),

• Alternatives to compare prevalences:

∙ Chi-square Test (this is a more traditional way),

∙ Fisher's Exact Test  (this is a better alternative),

∙ Unconditional Test  (most advanced, see Reiczigel et al. 2008.)   NEW (02. 01. 2010.)  

• Bootstrap t-Test to compare Mean Intensities,

• Mood’s Median Test to compare Median Intensities,

• Stochastic equality of intensity distributions (see Reiczigel et al. 2005b),

• Bootstrap t-Test to compare Mean Abundances,

• Comparison of Mean Crowding (see Reiczigel et al. 2005a),

3. To compare parasitic infections among samples of hosts:

• Descriptive statistics (N hosts, prevalence, mean & median intensity, variance/mean),

• Chi-square Test to compare Prevalences (this is a more traditional way),

• Fisher's Exact Test to compare Prevalences (this is a better alternative),

• Mood’s Median Test to compare Median Intensities.

Why do we apply several statistical tests in parallel with each other?

How to choose the approprite statistical procedures for a particular study?

Find a brief technical guide here.