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Sampling in Qualitative Research

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❶The following four-stage sampling procedure could be performed:

Contributions, Logic and Issues in Qualitative Sampling

Principles of Purposeful Sampling


This does, however, lead to a discussion of biases in research. For example, low-income children may be less likely to be enrolled in preschool and therefore, may be excluded from the study.

Extra care has to be taken to control biases when determining sampling techniques. There are two main types of sampling: The difference between the two types is whether or not the sampling selection involves randomization. Randomization occurs when all members of the sampling frame have an equal opportunity of being selected for the study.

Following is a discussion of probability and non-probability sampling and the different types of each. Probability Sampling — Uses randomization and takes steps to ensure all members of a population have a chance of being selected. There are several variations on this type of sampling and following is a list of ways probability sampling may occur:. Non-probability Sampling — Does not rely on the use of randomization techniques to select members. This is typically done in studies where randomization is not possible in order to obtain a representative sample.

Bias is more of a concern with this type of sampling. The different types of non-probability sampling are as follows:. The following Slideshare presentation, Sampling in Quantitative and Qualitative Research — A practical how to, offers an overview of sampling methods for quantitative research and contrasts them with qualitative method for further understanding. Examples of Data Collection Methods — Following is a link to a chart of data collection methods that examines types of data collection, advantages and challenges.

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Please review our privacy policy. To identify and select all cases that meet some predetermined criterion of importance.

Selection of consultant trainers and program leaders at study sites to facilitators and barriers to EBP implementation Marshall et al. Can be used to identify cases from standardized questionnaires for in- depth follow-up Patton, To identify and select all cases that exceed or fall outside a specified criterion. Selection of directors of agencies that failed to move to the next stage of implementation within expected period of time.

To illustrate or highlight what is typical, normal or average. A child undergoing treatment for trauma Hoagwood et al. The purpose is to describe and illustrate what is typical to those unfamiliar with the setting, not to make generalized statements about the experiences of all participants Patton, To describe a particular subgroup in depth, to reduce variation, simplify analysis and facilitate group interviewing. Often used for selecting focus group participants. To identify cases of interest from sampling people who know people that generally have similar characteristics who, in turn know people, also with similar characteristics.

To illuminate both the unusual and the typical. Selecting clinicians from state agencies or mental health with best and worst performance records or implementation outcomes. Extreme successes or failures may be discredited as being too extreme or unusual to yield useful information, leading one to select cases that manifest sufficient intensity to illuminate the nature of success or failure, but not in the extreme.

Same objective as extreme case sampling but with less emphasis on extremes. Clinicians providing usual care and clinicians who dropped out of a study prior to consent to contrast with clinicians who provided the intervention under investigation. Requires the researcher to do some exploratory work to determine the nature of the variation of the situation under study, then sampling intense examples of the phenomenon of interest.

Important shared patterns that cut across cases and derived their significance from having emerged out of heterogeneity. Investigation of a group of agencies that decided to stop using an evidence-based practice to identify reasons for lack of EBP sustainment. Particularly important when resources may limit the study of only one site program, community, population Patton, A sample is representative when it allows the results of the sample to be generalized to the population.

The sampling frame is the group of individuals who had a real chance of being selected for the sample. For example, if I use as my sampling frame the lists of students held by public and private schools in America from which to select a sample of adolescent females, then only students on those lists have a real chance of being selected. This may differ from the population to which I wish to generalize the results of my study all adolescent females in the United States.

In this case, my sample will almost certainly be bias because adolescent females with poor mental and with lower socio-economic status are probably less likely to be on school lists than other students.

As you can see from this example, the process of sampling , even when done systematically, can introduce potentially critical biases into a research study. Due our bias sampling technique we may enhance the risk of incorrectly concluding that there is no relationship between socioeconomic status and the mental health of adolescent females in the United States because we did representatively sample from adolescent females who weren't on school registers.

There are two main types of sampling - the key is whether or not the selection involves randomization. Randomization means that each unit within a sampling frame has an equal chance of being selected. By selecting randomly from a sampling frame , probability theory says that our sample, more often than not, should approximately represent the whole population. You can read more about sampling terminology and probability theory in social science research on Bill Trochim's Sampling Terminology page.

Probability sampling involves the use of randomization. These are the main types of probability sampling: Read Bill Trochim's Probability Sampling for more detailed explanations of the random probability sampling methods.

Non-probability sampling does not involve the use of randomization.


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Sampling and types of sampling methods commonly used in quantitative research are discussed in the following module. Learning Objectives: Define sampling and randomization. Explain probability and non-probability sampling and describes the different types of each.

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Probability sampling methods for quantitative studies In quantitative studies we aim to measure variables and generalize findings obtained from a representative sample from the total population. In such studies, we will be confronted with the following questions. Quantitative Research Definition: Quantitative research, in marketing, is a stimulating and highly educational technique to gather information from existing and potential customers using sampling methods and sending out online surveys, online polls, questionnaires etc., the results of which can be.

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experimental, quasi-experimental, and non-experimental quantitative research designs, Now it is time to deal with two more important aspects of quantitative reserach design: sampling, and. measurement. Key Terms. Sampling. sampling. sampling frame. of different sampling methods . Chapter 8: Quantitative Sampling I. Introduction to Sampling or reputational sampling) is a method for identifying and sampling the cases in a network. It begins with one is a special sampling technique used in research projects in which the general public is interviewed by telephone. Here is how RDD works in the United States.