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This study applied both random and non-random sampling strategies.
A non-random sampling design allowed to distinguish within a virgin beech ecosystem two main components of humus profile heterogeneity.
Typical for case study research is non-random sampling; there is no sample that represents a larger population.
This is still not the case in Italy, making it necessary to resort to non-random sampling methods.
We show how to enhance the statistical rigor of such a system by correcting a common non-random sampling problem encountered in the data.
The two variables were measured in two similar studies (N1=180, N2=169) which used non-random sampling and a non-experimental cross-correlational design.
To examine the properties of various approaches to estimation we carry out a simulation study, looking at bias due to both non-response and non-random sampling.
The paper discusses the methodological implications of these differences and evaluates different methodological solutions based on both random and non-random sampling methods in both countries.
The sample consisted of 30 adults with type 2 diabetes mellitus in the experimental group and 30 in the control group of the two private hospitals selected by convenience non-random sampling technique.
The sample consisted of 30 diabetic adults in the experimental group and 30 in the control group attending the outpatient departments in the two private hospitals selected by convenience non-random sampling technique.
Non-random sampling may also have overestimated the level of HIV-related knowledge seen in the results.
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