Sampling 1 Biostatistics

8/8/2019 Sampling 1 Biostatistics

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SamplingSampling


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PopulationPopulation

All the inhabitants of a given country or area

considered together; the number of inhabitants of a

given country or area The population is all elements (individuals, objective,

or substance) that meet certain criteria for inclusions

in a study (Kerlinger, 1986).


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PopulationPopulation

Target Population

The group from which the study population is selected

Study Population The group selected for investigation

Elements of a population

The subject on which the measurement is collected


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SamplingSampling

Sample

A sample is a subset of the population that is

selected for a particular study, and the members of

a sample are the subjects.


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SamplingSampling

Sampling

The process of selecting a number from all the subjects

is a process of selecting subjects who are representative of thepopulation being studied

Sampling frameList of Participants


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Probability SamplingProbability Sampling

Is a method of sampling that utilizes

some form ofrandom selection. In order

to have a random selection method, youmust set up some process or procedure

that assures that the different units in

your population have equal probabilities

of being chosen.


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Stratified Random SampleStratified Random Sample

A stratified random sample is one obtained

by separating the population elementsinto non-overlapping groups, calledstrata, and then selecting a simplerandom sample from each stratum.


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Systematic Random SamplingSystematic Random Sampling

Number the units in the population from 1 to

N decide on the n (sample size) that you

want or need k = N/n = the interval sizerandomly select an integer between 1 to k

then take every kth unit


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All of this will be much clearer with an

example. Let's assume that we have a

population that only has N=100 people in itand that you want to take a sample of n=20.

To use systematic sampling, the population

must be listed in a random order. The

sampling fraction would be f = 20/100 = 20%

in this case, the interval size, k, is equal to

N/n = 100/20 = 5.


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Now, select a random integer from 1 to 5. In

our example, imagine that you chose 4.Now, to select the sample, start with the 4th

unit in the list and take every k-th unit

(every 5th, because k=5). You would be

sampling units 4, 9, 14, 19, and so on to

100 and you would wind up with 20 units

in your sample.


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Cluster SamplingCluster Sampling

Divide population into clusters (usually along

geographic boundaries)

Randomly sample clusters

Measure all units within sampled clusters


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Cluster SamplingCluster Sampling

is a probability samplein which eachsample unitisa collection, or cluster, of

elements. Thefirsttaskin clustersampling istospecify appropriate clusters.

Elements withina clusterareoftenphysically closetogetherand hencetenttohavesimilar characteristics.


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Non Probability samplingNon Probability sampling

Convenience sampling

Quota Sampling

Purposive sampling

Network Sampling


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Convenience samplingConvenience sampling

is used in exploratory research where the

researcher is interested in getting an inexpensive

approximation of the truth. As the name implies,the sample is selected because they are

convenient. This non-probability method is often

used during preliminary research efforts to get agross estimate of the results, without incurring

the cost or time required to select a random

sample.


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Quota SamplingQuota Sampling

It uses a convenience sampling technique

with added feature - a strategy to ensure the

inclusion of subjects types who are likely tobe underrepresented in the convenience

sample e.g. ethnicity , Hindu religion in

Pakistan


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Quota samplingQuota sampling

is the non-probability equivalent of stratifiedsampling. Like stratified sampling, the

researcher first identifies the stratums and theirproportions as they are represented in thepopulation. Then convenience or judgmentsampling is used to select the required number of

subjects from each stratum. This differs fromstratified sampling, where the stratums are filledby random sampling.


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Purposive /JudgmentPurposive /Judgment

SamplingSampling

is a common non-probability method. Theresearcher selects the sample based on judgment.

This is usually and extension of conveniencesampling. For example, a researcher may decideto draw the entire sample from one"representative" city, even though the population

includes all cities. When using this method, theresearcher must be confident that the chosensample is truly representative of the entirepopulation.


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Network / Snowball SamplingNetwork / Snowball Sampling

is a special non-probability method used when thedesired sample characteristic is rare. It may beextremely difficult or cost prohibitive to locate

respondents in these situations. Snowball samplingrelies on referrals from initial subjects to generateadditional subjects. While this technique candramatically lower search costs, it comes at the

expense of introducing bias because the techniqueitself reduces the likelihood that the sample willrepresent a good cross section from the population.

Sampling 1 Biostatistics

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