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Pseudoreplication and Ecology

Pseudoreplication and Ecology. Dr. James A. Danoff-Burg Columbia University. Purposes of Replication. Controls for random or stochastic error E.g., untested independent factors may otherwise determine the outcome of the experiment Increases the precision of the test

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Pseudoreplication and Ecology

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  1. Pseudoreplication and Ecology Dr. James A. Danoff-Burg Columbia University

  2. Purposes of Replication • Controls for random or stochastic error • E.g., untested independent factors may otherwise determine the outcome of the experiment • Increases the precision of the test • Increases the generalizability of the test • If you test across many sites – you can safely generalize to many others

  3. Some Definitions • Replicate = Sample • Maximize these in your experimental design • Greatest number possible, given logistical limitations • If you are a professional, use a power analysis • Subsample = Pseudoreplicate • Only true if the subsamples are incorrectly treated as true replicates for statistical analysis • Subsamples: useful to increase the accuracy of the data estimate for that replicate • A special type of statistical analysis are therefore possible

  4. Pseudoreplication - Defined • Incorrect “replication” • Replicating samples, not treatments • Replicates are not independent • Problem is that it violates a key assumption of statistical analysis: • Independence of replicates • Increasing precision of studies if independent • Approximates “truth” better if independent

  5. Prevalence of Pseudoreplication • 48% of all studies had pseudoreplication (Hurlbert 1984) • 71% of studies using ANOVA (a common statistical test) had design errors (Underwood 1981) • Particularly acute in studies with logistical problems • Rare animals • Transportational or financial limitations • Many of ours!

  6. Examples • Many samples from a single site • These are actually subsamples • Only a single sample for each treatment condition • These are actually replicates, but cannot do statistics on a sample size of one • Single samples from a single site, but replicated in time • Would be true samples if the experimental question is time-dependent • If not, it is pseudoreplication

  7. Pseudoreplication Example Treatment A Treatment B • Question – What is the affect of treatments A & B? • Pseudoreplication = treating stars of the same color as replicates • Replication = include only a single star of each color Site 3 Site 1 Site 2 Site 4

  8. Controlling Pseudoreplication I • Know your question • Question determines whether design includes pseudoreplication • Taxonomic level • Ecological hierarchy level • Clearly define your independent and dependent variables

  9. Controlling Pseudoreplication II • What constitutes a unit of data? • Plant branch? Individual? Population? Etc.? • Identify what is the unit of replication • Individual? Population? Community? Site? • Replicate accordingly – sites are often the level of replication for our projects • Randomize your sampling design • Helps to decrease sampling errors

  10. For Our Class • We will frequently use pseudoreplication • Limitations on time (only 4 weekends for our work!) • Limitations on transportation (only 1 van!) • Limitations on effort (only you!) • Consequently • We will frequently treat our pseudoreplicates as true replicates • However – be aware of this and you will be fine when you design more robust research projects in the future

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