Week 7

35問 • 1年前

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is the overall plan for obtaining answers to the research questions. Quantitative designs tend to be structured and controlled, with the goal of minimizing bias. The research design is the architectural backbone of the study.

research design

for the study must be developed, specifying exactly what the intervention will entail (e.g., who will administer it, over how long a period the treatment will last, and so on) and what the alternative condition will be. In non-experimental research, this step is not necessary.

intervention protocol

is all the individuals or objects with common, defining characteristics

population

Researchers specify population characteristics through

eligibility criteria

Researchers establish criteria to determine whether a person qualifies as a member of the population or should be excluded.

inclusion criteria, inclusion criteria

involves selecting cases (sample) to represent the population.

Sampling

A ?, is a subset of the population.

sample

are subpopulations, mutually exclusive segments of a population based on a specific characteristic.

Strata

A specifies how the sample will be selected and how many subjects there will be. The goal is to have a sample that adequately reflects the population’s traits.

sampling plan

Well-designed samples allow researchers to apply findings from the sample to the entire population.

Generalizability

Sampling is more practical and cost-effective than studying the entire population.

Cost-Effectiveness

. Careful sampling minimizes bias, improving the validity of the research results.

Accuracy

Sample elements are selected by nonrandom methods in which every element does not have an equal chance to be included. This can introduce bias, but it is sometimes used for exploratory research.

Nonprobability Sampling

involves random selection of elements from a population. Each element in the population has an equal, independent chance of being selected. This reduces bias and increases generalizability.

Probability Sampling

selecting the most conveniently available people as participants. studies. It is the weakest form of sampling, but it is also the most commonly used.

Convenience Sampling

researchers identify population strata and figure out how many people are needed from each stratum.

Quota Sampling

involves recruiting all people from an accessible population over a specific time interval or for a specified sample size.

Consecutive Sampling

involves using researchers’ knowledge about the population to handpick sample members.

Purposive Sampling

early sample members are asked to identify and refer other people who meet the eligibility criteria.

Snowball Sampling

The most basic of the probability sampling plans. It is achieved by randomly selecting elements from a sampling frame.

Simple Random Sampling

A is a list of every member of the population using the sampling criteria to define eligibility. The list of elements from which the sample will be chosen.

Sampling Frame

The population is first divided into two or more strata, from which elements are randomly selected. Like with quota sampling, the aim of stratified sampling is to enhance representativeness.

Stratified Random Sampling

involves the selection of every nth case from a list, such as every 10th person on a patient list. Systematic sampling can be done so that an essentially random sample is drawn.

Systematic Sampling

Larger populations generally require larger samples.

Population Size

How much error you are willing to tolerate (smaller margins require larger samples). Commonly set at 0.05 or 5%.

Margin of Error

Usually 95% (represented by a Z-value of 1.96 in statistical formulas).

Confidence Level.

. The variability within the population. If unsure, a 50% variance is often used for conservative estimates.

Variance

ensures that your sample size is large enough to provide reliable, statistically significant results without surveying the entire population, making it a powerful tool for survey research.

Cochran's formula

Qualitative research seeks to understand how and why things happen, rather than quantifying outcomes. The sample size should be large enough to ensure data saturation but small enough to manage the depth of analysis required.

Purpose of the Study.

. Saturation is reached when no new information or themes are emerging from the data. Once the researcher notices repetitive patterns, the sample size is considered sufficient. •Studies typically report achieving saturation anywhere from 5 to 30 participants.

DATA SATURATION. S

. Often involves 5-10 participants, focusing on deep exploration of lived experiences.

Phenomenology

. May require 20-30 participants or more, as it aims to develop a theory from the data.

Grounded Theory.

. Depending on the depth of immersion in a culture or setting, this can vary greatly, but usually fewer participants are studied intensively over a long period.

Ethnography

. A single case study might focus on 1-5 cases, with detailed analysis of each case.

Case Study.

Resources (time, budget, and availability of participants) ofteninfluence sample size decisions. Small, manageable sample sizes are often used in qualitative research because of the intensive nature of data collection (e.g.,interviews, focus groups, observations) and analysis.

Pragmatic Considerations in Qualitative Sampling.

Latin Abbreviations

JULLIANNE DANDAN · 43問 · 2年前

Latin Abbreviations