📊Sampling Surveys Unit 10 – Data Collection Methods

Key Concepts and Definitions

• Data collection involves gathering and measuring information on variables of interest to answer research questions, test hypotheses, and evaluate outcomes
• Sampling is the process of selecting a subset of individuals from a larger population to estimate characteristics of the whole population
• A sampling frame is a list of all members of a population from which a sample can be drawn
• Probability sampling uses random selection, giving each member of the population an equal chance of being included in the sample
• Non-probability sampling relies on the researcher's judgment or convenience to select participants, which may introduce bias
• Response rate is the proportion of individuals who complete a survey out of the total number invited to participate
• Validity refers to the extent to which a survey measures what it intends to measure
• Reliability is the consistency of survey results across different administrations or over time

Types of Data Collection Methods

• Surveys gather information through questionnaires or interviews administered to a sample of individuals
  • Can be conducted online, by phone, mail, or in-person
  • Allow for large sample sizes and standardized data collection
• Observations involve systematically watching and recording behavior without direct interaction with subjects
  • Can be structured (using predetermined categories) or unstructured (open-ended)
  • Provide insights into natural behaviors and contexts
• Experiments manipulate one or more variables to determine their effect on a dependent variable
  • Participants are randomly assigned to treatment and control groups
  • Enable causal inferences by controlling for confounding variables
• Interviews are in-depth, one-on-one conversations with participants to explore their experiences, opinions, or knowledge
  • Can be structured (fixed questions), semi-structured (mix of predetermined and follow-up questions), or unstructured (open-ended)
• Focus groups bring together a small group of individuals to discuss a topic guided by a moderator
  • Provide qualitative data on attitudes, perceptions, and group dynamics
• Secondary data analysis uses existing data sources (census data, administrative records) to answer new research questions
  • Cost-effective and time-efficient, but limited by the quality and relevance of available data

Survey Design Principles

• Define clear research objectives and target population before designing the survey
• Use simple, unambiguous language in questions to ensure consistent interpretation by respondents
• Avoid leading or loaded questions that bias responses in a particular direction
• Provide mutually exclusive and exhaustive response options for closed-ended questions
• Use open-ended questions sparingly to gather additional insights or explanations
• Organize questions in a logical flow, starting with general questions and moving to more specific or sensitive topics
• Pilot test the survey with a small sample to identify and address any issues with question wording, order, or length
• Keep surveys concise to minimize respondent fatigue and improve completion rates

Sampling Techniques

• Simple random sampling selects participants at random from a sampling frame, giving each individual an equal chance of being chosen
• Stratified sampling divides the population into homogeneous subgroups (strata) based on key characteristics (age, gender) and then randomly samples from each stratum
  • Ensures representation of important subgroups and improves precision of estimates
• Cluster sampling divides the population into clusters (geographic areas, organizations), randomly selects a subset of clusters, and then samples all individuals within chosen clusters
  • More cost-effective than simple random sampling for geographically dispersed populations
• Systematic sampling selects every nth individual from a sampling frame after a random starting point
  • Easier to implement than simple random sampling but may introduce bias if sampling interval is related to the variable of interest
• Convenience sampling selects participants based on their availability and willingness to participate
  • Prone to selection bias and may not be representative of the target population
• Snowball sampling recruits initial participants who then refer other potential participants from their social networks
  • Useful for hard-to-reach or hidden populations but may overrepresent individuals with larger social networks

Questionnaire Development

• Begin with a clear statement of purpose and instructions for completing the survey
• Use a mix of closed-ended questions (multiple choice, Likert scales) for quantitative analysis and open-ended questions for qualitative insights
• Ensure questions are relevant to research objectives and provide sufficient information to answer them
• Avoid double-barreled questions that ask about two separate issues in a single question
• Use skip logic to direct respondents to relevant questions based on their previous answers
  • Minimizes irrelevant questions and reduces survey length
• Provide "don't know" or "not applicable" options to prevent forced responses
• Use consistent scales and response formats throughout the questionnaire
• Include demographic questions at the end of the survey to describe the sample and conduct subgroup analyses

Data Collection Tools and Technology

• Online survey platforms (Qualtrics, SurveyMonkey) allow for quick and cost-effective distribution to large samples
  • Offer features like skip logic, randomization, and real-time data analysis
  • May exclude individuals without internet access or digital literacy skills
• Computer-assisted telephone interviewing (CATI) systems automate the process of conducting phone surveys
  • Interviewers read questions from a computer screen and enter responses directly into a database
  • Enables complex skip patterns and reduces data entry errors
• Audio computer-assisted self-interviewing (ACASI) allows respondents to complete surveys on a computer while listening to questions through headphones
  • Increases privacy and reduces social desirability bias for sensitive topics
• Mobile data collection tools (ODK, KoBoToolbox) enable offline data collection on smartphones or tablets
  • Useful for field research in low-connectivity settings
  • Can incorporate GPS, photos, and other multimedia data

Ethical Considerations

• Obtain informed consent from participants, disclosing the purpose, procedures, risks, and benefits of the study
• Protect participant confidentiality by anonymizing data and using secure storage and transmission methods
• Minimize potential harm or discomfort to participants, especially when studying sensitive topics or vulnerable populations
• Provide participants with the right to withdraw from the study at any time without penalty
• Avoid deceptive practices that mislead participants about the true nature of the research
• Ensure equitable selection of participants and avoid exploitation of disadvantaged groups
• Obtain approval from institutional review boards (IRBs) or ethics committees before conducting research with human subjects
• Disseminate research findings accurately and transparently, acknowledging limitations and potential biases

Challenges and Limitations

• Nonresponse bias occurs when individuals who respond to a survey differ systematically from those who do not respond
  • Can be addressed through follow-up reminders, incentives, and weighting techniques
• Measurement error arises when survey questions fail to accurately capture the intended construct
  • Can be minimized through careful question design and pretesting
• Social desirability bias leads respondents to provide answers that present themselves in a favorable light
  • Can be reduced through self-administered surveys and neutral question wording
• Recall bias occurs when respondents have difficulty accurately remembering past events or behaviors
  • Can be mitigated by using shorter reference periods and aided recall techniques
• Interviewer effects can influence responses through characteristics or behaviors of the interviewer
  • Can be minimized through standardized interviewer training and monitoring
• Coverage error occurs when the sampling frame does not adequately represent the target population
  • Can be addressed by using multiple sampling frames or post-stratification weighting
• Sampling error arises from studying a subset of the population rather than the entire population
  • Can be quantified through confidence intervals and reduced by increasing sample size