Non-Probability and Probability Sampling Methods

Methods of Non-Probability Sampling

• Convenience Sampling: Utilizes readily available subjects for sample selection; involves accidental sampling and snowball/network sampling.
• Snowball Sampling: Initial subjects identify other potential eligible participants; useful in hard-to-reach populations.
• Quota Sampling: Researcher sets specific population strata and proportions; samples are obtained through convenience sampling (e.g., a sample with 15% males and 85% females).
• Purposive Sampling: Involves handpicking subjects based on the researcher's understanding of the population; also known as judgment sampling.
• Theoretical/Thematic Sampling: Focuses on in-depth qualitative research; ensures representation of relevant themes related to the studied phenomenon.

Methods of Probability Sampling

• Simple Random Sampling: Elements are selected randomly from a defined sampling frame.
• Stratified Random Sampling: Population is divided into strata; samples are randomly taken within each subgroup for enhanced representativeness.
• Cluster Sampling/Multi-Stage Sampling: Involves successive random sampling of large group units; clusters can be selected through simple or stratified methods.
• Systematic Sampling: Every nth case is selected from a list (e.g., every 10th person); provides a systematic approach to sampling.

Sample Size Considerations

• Design Type Impact:
  • Descriptive Studies require 10% of the population (min 20% for smaller populations).
  • Correlation Studies generally use 30 subjects.
  • Experimental Studies typically require 15 subjects per group.
• Sampling Procedure and Formula:
  • Various formulas such as Slovin’s formula help estimate the optimum sample size.
  • Rule of 30 suggests a minimum of 30 subjects.
  • Rule of 10 indicates 10 samples for each variable in study.
• Influencing factors include desired precision, population heterogeneity, frequency of the phenomenon, and cost associated with the sampling strategy.

Empirical Phase

• Data Collection: This phase involves gathering information relevant to the research.

Data Collection Methods

• Existing Data Usage: Leverages pre-existing data sources for research, including hospital records, patient charts, and reports.
• Self-Reports: Commonly used in both quantitative and qualitative research; data can be gathered through interviews or questionnaires.
  • Provides direct and versatile data but may face validity issues due to participants' reluctance to disclose private information.

Review of Related Literature

• Literature Review Purposes:
  • Helps identify research problems and refine research questions/hypotheses.
  • Assesses existing literature for gaps or inconsistencies.
  • Evaluates the need for replication in different settings to strengthen theories.
  • Informs the development of new clinical interventions.
  • Aids in selecting appropriate research designs and data collection methods.
  • Identifies experts in the relevant field for further collaboration or insight.