What is pseudoreplication in experimental design?

What is pseudoreplication in experimental design?

Pseudoreplication is defined as the use of inferential statistics to test for treatment effects with data from experiments where either treatments are not replicated (though samples may be) or replicates are not statistically independent. The critical features of controlled experimentation are reviewed.

How do you avoid pseudoreplication?

In the first two examples, the experimental design is relatively straightforward and pseudoreplication can be avoided simply by identifying the indepen- dent experimental units and applying design-based inference solely to these.

Why is pseudoreplication a big problem in experimental design?

Pseudoreplication leads to the wrong hypothesis being tested and false precision. Ignoring lack of independence leads to two major problems. The first is that the statistical analysis is not testing the research hypothesis that the scientist intends, in other words, the incorrect hypothesis is being tested.

How do you deal with pseudoreplication?

The two main ways of dealing with pseudoreplication are: (1) average the pseudoreplicates to obtain one value per genuine replicate, or (2) use a more sophisticated approach that captures the structure of the data where the pseudoreplicates are nested under the genuine replicates, such as a multilevel/hierarchical …

What is an example of pseudoreplication?

Here are some other examples of pseudoreplication: treating multiple leaves from the same plant as replicates; treating multiple plants from the same pot or flat as replicates; treating multiple samples from the same plot as replicates.

What causes pseudoreplication?

Implicit pseudoreplication occurs when standard errors (or confidence limits) are estimated within experimental units. As with other sources of pseudoreplication, treatment effects cannot be statistically separated from effects due to variation among experimental units.

What is pseudoreplication example?

What causes Pseudoreplication?

What is temporal Pseudoreplication?

g) Temporal pseudoreplication occurs when multiple samples are taken from each experimental unit sequentially over time, and the sampling dates are taken to represent replicated treatments.

What is a true replicate?

True replication permits the estimation of variability within a treatment. Without estimating variability within treatments, it is impossible to do statistical inference. Consider, for example, comparing two drugs by trying drug A on person 1 and drug B on person 2.

What is meant by pseudoreplication?

Pseudoreplication is the process of artificially inflating the number of samples or replicates. As a result, statistical tests performed on the data are rendered invalid. Hurlbert reported “pseudoreplication” in 48% of the studies he examined, that used inferential statistics.

Why is pseudoreplication used?

Pseudoreplication has been defined as the use of inferential statistics to test for treatment effects with data from experiments or observational studies where either treatments are not replicated (though samples may be) or replicates are not statistically independent.

Is it possible to avoid the error of pseudoreplication?

Pseudoreplication is simply a mistake, and it always can and should be avoided if at all possible. The error is in regarding that test as being of some treatment effect for which there is no independent replication.

Where did the term pseudo replication come from?

The term pseudo-replication was coined by Hurlbert to refer to “the use of inferential statistics to test for treatment effects with data from experiments where either treatments are not replicated (though samples may be) or replicates are not statistically independent.” making it a classic paper within ecology.

Who was the first person to use the term pseudoreplication?

The term ‘pseudoreplication’ was first introduced by Hurlbert (1984) in one of the most widely cited publications of all time. However, a number of ecologists have since taken issue with Hurlbert, especially in relation to terminology, and the need to distinguish the issues of replication and independence.

When to use pseudoreplication in an observational study?

Simple pseudoreplication is probably most common in observational studies – especially multiple group studies. If random samples are taken from one polluted area and one unpolluted area, they can validly be used to compare the two areas, but not to examine the effect of pollution.