PR 1

• Sampling


  The process by which a researcher identifies the representative of a population to be used in his/her study
• Probability/Statistical Sampling


  • Used when an accurate representation of the entire population is needed in the sample
  • Gives all representatives of the entire population to be selected as a sample
  • Often used in quantitative research rather than qualitative research
• Non-probability Sampling


  • Used when the population can not/does not need to be sampled to represent the target population
  • Individuals do not have an equal chance of being sampled
  • Often used in qualitative research rather than quantitative research
• Types of validity

  • Concurrent Validity
  • Predictive Validity
  • Convergent Validity
  • Discriminant Validity
• Types of Sampling Methods

  • Probability/Statistical Sampling
  • Non-Probability Sampling
• Simple Random Sampling

  • Samples are identified randomly with the help of statistical and mathematical computations.
• Stratified Random Sampling

  • The population is divided into different groups/strata based on criteria set by the researcher. The researcher then randomly identifies individuals from these groups.
• Cluster Sampling

  • This is similar to stratified randomly sampling, but instead of grouping them based on criteria set by the researchers the individuals are randomly selected from naturally occurring groups (e.g. sections in a school)
• Multistage Sampling

  • This type of sampling is a combination of stratified random and cluster sampling. It consists of multiple stages of grouping: first from naturally occurring groups and then groups based on criteria set by the researcher.
• Systematic Sampling

  • This method of sampling is the easiest since it only requires the researcher to set a fixed interval to determine the sample.
• Types of Probability/Statistical Sampling

  • Simple Random Sampling
  • Stratified Random Sampling
  • Cluster Sampling
  • Multistage Sampling
  • Systematic Sampling
• Types of Non-Probability Sampling

  • Purposive Sampling
  • Convenience Sampling
  • Snowball Sampling
  • Quota Sampling
• Purposive Sampling

  • Samples are targeted and selected based on a criterion set by the researcher. These criteria are based on the research objectives and questions that the study aims to answer.
• Convenience Sampling

  • The sampling group is identified by the convenience of the researcher. Groups are determined based on their availability rather than randomness from the population. This method of sampling does not guarantee an accurate representation of the population but can be useful in collecting preliminary data.
• Snowball Sampling

  • The identification of the sample group is accumulative and can come from populations not initially known by the researcher. They can ask the patients they know for others like them.
• Quota Sampling

  • Very similar to purposive sampling wherein the population is filtered based on a criterion set by a researcher. However, they are looking for specific characteristics in individuals that may or may not directly link to the research question/objective.
• Data Cleaning/Preparation


  Transform data into manageable formats, identify relevant and usable data
• 4 Repetitive Steps of Data Exploration

  1. Chunking

  2. Clustering

  3. Coding

  4. Memoing
• Chunking


  Breaking down cleaned data and determining purpose of each part
• Clustering


  Classifying chunks according to labels or basic codes
• Coding


  Creating labels and categories that represent data accurately, move from descriptive to interpretative to pattern
• Memoing


  Taking codes and clusters and adding notes to explain or define them
• Methods of Data Interpretation and Presentation

  1. Narrative

  2. Chronological

  3. Critical Incidents

  4. Thematic

  5. Visual representation
• Validity


  Verify or check if data collected is accurate and can support proposed discussions
• Concurrent Validity


  Relates results to an already established/validated set of scores
• Predictive Validity


  Relates results to a future criterion to predict some form of behavior
• Convergent Validity


  Determines the correlation of different results, tests the relationship among variables
• Discriminant Validity


  Determines the lack of relationship among certain variables according to theory and empirical evidence
• Narrative – focused on telling a story using the results.
• Chronological – according to the narrative described by each

  participant. Useful in case studies.
• Critical Incidents – focused on the main incidents, not the

  participants
• Thematic – data is presented in a way that it revolves around

  a particular theme
• Visual representation – data can be presented as charts or tables. It should be thought of carefully when being used in qualitative research.