Sampling Techniques. Esra Akdeniz. February 9th, 2016

Transcription

1 Sampling Techniques Esra Akdeniz February 9th, 2016

2 HOW TO DO RESEARCH? Question. Literature research. Hypothesis. Collect data. Analyze data. Interpret and present results.

3 HOW TO DO RESEARCH? Collect data.

4 WHAT IS DATA? Data is a collection of facts, such as values or measurements. It can be numbers, words, measurements, observations or even just descriptions of things.

5 Sample A sample is a group of units that are actually measured. A population is the entire group of units about which an inference will be made.

6 Sample A sample is a group of units that are actually measured. A population is the entire group of units about which an inference will be made. Why do we need samples?

7 Sample A sample is a group of units that are actually measured. A population is the entire group of units about which an inference will be made. Why do we need samples? To make inference. A sample needs to be representative of the population.

8 Sample A sample is a group of units that are actually measured. A population is the entire group of units about which an inference will be made. Why do we need samples? To make inference. A sample needs to be representative of the population. Sample size is the total number of units in the sample.

9 Sampling Terminology Study units or sampling units: Individual elements in the population of interest.

10 Sampling Terminology Study units or sampling units: Individual elements in the population of interest. Target population: The ideal population we would like to describe. Study population: After we account for practical constraints, the group from which we can actually sample from.

11 Sampling Terminology Study units or sampling units: Individual elements in the population of interest. Target population: The ideal population we would like to describe. Study population: After we account for practical constraints, the group from which we can actually sample from. Sampling frame: A list of the elements in the study population.

12 Sampling Terminology Study units or sampling units: Individual elements in the population of interest. Target population: The ideal population we would like to describe. Study population: After we account for practical constraints, the group from which we can actually sample from. Sampling frame: A list of the elements in the study population. Selection bias: A systematic tendency to exclude certain members of the target population.

13 Example Average amount of cigarettes smoked by 20-to 30-year olds living in Istanbul. Sampling unit Target population Study population Sampling frame

14 Sampling Techniques Simple Random Sampling Systematic Sampling Stratified Sampling Cluster Sampling Nonprobability Sampling

15 Simple Random Sampling Units are independently selected, one at a time until the desired sample size is achieved. Sampling without replacement. Each unit has an equal chance of being selected. The change of being selected is n/n, sampling fraction of the population. Random number generators, table of random numbers.

16 Systematic Sampling A complete list of N elements in the population is available. Sampling fraction is n/n OR 1/(N/n) OR 1 in N/n. Initial sample unit is selected from the first k units, then the rest is i + k, i + 2k, and so on.

17 Systematic Sampling A complete list of N elements in the population is available. Sampling fraction is n/n OR 1/(N/n) OR 1 in N/n. Initial sample unit is selected from the first k units, then the rest is i + k, i + 2k, and so on. Advantages: Requires only one random number selection, distributes the sample evenly over the entire population list.

18 Stratified Sampling Takes into account certain characteristics of the population. Divide the population into H distinct subgroups, strata, such that hth stratum has size N h. Select a simple random sample of size n h from each distinct group. Each stratum has a sampling fraction of n h /N h.

19 Stratified Sampling Takes into account certain characteristics of the population. Divide the population into H distinct subgroups, strata, such that hth stratum has size N h. Select a simple random sample of size n h from each distinct group. Each stratum has a sampling fraction of n h /N h. Advantages: Each distinct subgroup is represented in the sample.

20 Stratified Sampling Takes into account certain characteristics of the population. Divide the population into H distinct subgroups, strata, such that hth stratum has size N h. Select a simple random sample of size n h from each distinct group. Each stratum has a sampling fraction of n h /N h. Advantages: Each distinct subgroup is represented in the sample. Each member of the population has an equal chance of being sampled?

21 Cluster Sampling Study units form natural groups, clusters, such as districts in a city. Two-stage sampling: 1. Select a random sample of clusters. 2. Select a random sample within each cluster.

22 Cluster Sampling Study units form natural groups, clusters, such as districts in a city. Two-stage sampling: 1. Select a random sample of clusters. 2. Select a random sample within each cluster. Advantage: More economical than other types of sampling; saves both time and money.

23 Cluster Sampling Study units form natural groups, clusters, such as districts in a city. Two-stage sampling: 1. Select a random sample of clusters. 2. Select a random sample within each cluster. Advantage: More economical than other types of sampling; saves both time and money. Stratified versus Cluster sampling.

24 Nonprobability Sampling Probability of an individual being included is unknown. Convenience sample and samples made up of volunteers.

25 Nonprobability Sampling Probability of an individual being included is unknown. Convenience sample and samples made up of volunteers. Problem: Bias and not representative.

26 Source of Bias Nonresponse. Lying to sensitive questions.

27 Source of Bias Nonresponse. Lying to sensitive questions. How to deal with these? Missing data techniques and other survey methods.

28 Examples Colon cancer patients in Turkey. Smokers between the ages of 21 and 30 in the Black Sea region.

29 Summary Target population and study population. Characteristics of your sample. Sampling technique.