Quantitative Parasitology 3.0

 

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.

 

Download

and isntall QP3.0

(a self-executive exe file and other files in a zipped folder)

 

or go to our new

QP on the Web

 (an interactive web surface)

 

 

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

 

QP3.0 runs under Windows. After download, unzip the file and find a folder named 'QP30'. Do not remove the files from the folder. Within this folder, you just

  

     •  right click (i.e. use the right mouse button to click) the file named '_qp30.exe'

     •  then select 'run as administrator'.

 


 

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

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

  Find a brief technical guide here.

 


 

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),

Two 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),

Two 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 3 or more samples of hosts:

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

Two alternatives to compare prevalences:

          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 to 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.

 


 

Further readings

 

Some of the methods listed above have been described or discussed in the following articles. Please cite them in relation to the appropriate methods.

 

 Reiczigel J 2003. Confidence intervals for the binomial parameter: some new considerations. Statistics in Medicine 22: 611-621.

 Reiczigel J, Lang Z, Rózsa L, Tóthmérész B 2005. Properties of crowding indices and statistical tools to analyze crowding data. Journal of Parasitology 91: 245-252.

 Reiczigel J, Zakariás I, Rózsa L 2005. A bootstrap test of stochastic equality of two populations. The American Statistician 59: 156-161.

 Reiczigel J, Abonyi-Tóth Z, Singer J 2008. An exact confidence set for two binomial proportions and exact unconditional confidence intervals for the difference and ratio of proportions. Computational Statistics and Data Analysis 52: 5046-53.

 


  

Bug fixed

There was a mistake slightly affecting the confidence intervals for mean intensity and mean abundance in a former version of Quantitative Parasitology. QP2.0 downloaded after 02. 04. 2003. and all copies of QP 3.0 are free of this error.

  

Contacts

Mail to reiczigel.jeno (at) gmail.com regarding biostatistics and computation; or mail to lajos.rozsa (at) gmail.com regarding epidemiology or biology.

  

Supported by

Hungarian Academy of Sciences, Hungarian National Scientific Research Found (OTKA T 049157), Szent István University (NKB 2001-KUT-5-018)

  

Copyright Notice

The papers listed above has been published at different peer-reviewed journals. Copyright and all rights therein are retained by the respective publishers. This material may not be copied or reposted without explicit permission. Use for scholarly and educational purposes only.

 

This page is on-line since 27th of Nov, 2001.  

  Last updated on the 11th of July, 2014.

  Maintained by Lajos Rózsa.

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