MichiGau: Created page with "=== Description === choose target population and a strategy of how to choose samples related to the unit of analysis in a research problem avoid a biased sample ==== Sampli..."

2020-03-20T08:12:48Z

Created page with "=== Description === choose target population and a strategy of how to choose samples related to the unit of analysis in a research problem avoid a biased sample ==== Sampli..."

New page

=== Description ===
choose target population and a strategy of how to choose samples
related to the unit of analysis in a research problem
avoid a biased sample

==== Sampling approaches: ====

'''Probability sampling:'''
* technique in which every unit in the population has a chance (non-zero probability) of being selected
* chance to be selected can be accurately determined
* sampling procedure involves random selection at some point
methods: random sampling, systematic sampling, stratified sampling, cluster sampling, matched pairs sampling, multi-stage sampling

'''Non-probability sampling:'''
* some units of the population have either zero chance of selection or the probability of selection cannot be determined accurately
* selection criteria are non-random (e.g. quota, convenience)
* estimation of sampling errors is not allowed
* information from a sample cannot be generalized back to the population
methods: convenience sampling, snowball sampling, quota sampling, expert sampling
=== Examples ===
==== Probability sampling: ====

Cluster sampling:
* divide population into clusters
* randomly sample a few clusters and measure all units within that cluster

Matched pairs sampling:
* two subgroups of population
* compare two individual units from subgroups with other
* ideal way to understand bipolar differences

Multi-stage sampling:
* combine the previously described sampling technique
* e.g. combine cluster and random sample

Random sampling:
* all subsets are given equal probability of being selected
* unbiased estimates of population parameters

Stratified sampling:
* divided into homogeneous and non-overlapping subgroups
* simple random sample within each subgroup

Systematic sampling:
* sampling frame is ordered according to some criteria
* elements are selected at regular intervals

==== Non-probability sampling: ====

Convenience sampling:
* take a sample from a population that is close to hand
* e.g. outside of shopping mall
* may not be representative, therefore limited generalization

Expert sampling:
* choose respondents in a non-random manner based on their expertise on the phenomenon
* findings are still not generalizable to a population
* e.g. in-depth study on an institutional factor such as Sarbanes-Oxley Act

Quota sampling:
* segment population into mutually exclusive subgroups
* take a non-random set of observations to meet pre-defined quota
* pre-defined quota can either proportional (as the overall population) or non-proportional (less restrictive)
* both are not representative of the population

Snowball sampling:
* start criteria-based
* ask respondents for further potential participants
=== Further Readings ===
[1] Bhattacherjee, A. (2012). "Social Science Research: Principles, Methods, and Practices", Textbooks Collection. 3. Available at: https://scholarcommons.usf.edu/oa_textbooks/3

Template:Sampling Strategy - Revision history

MichiGau: Created page with "=== Description === choose target population and a strategy of how to choose samples related to the unit of analysis in a research problem avoid a biased sample ==== Sampli..."