STATS Lecture 2

Population

particular group of individuals who are being studied (i.e. people with diabetes)

Target population

determined by sample criteria

accessible population

sample within the target population

Sample

focus of a particular study

Study elements

participants, subjects, objects, or events that might be included in the sample for a study

Sample Size

must be of adequate size to determine significant relationships among variables of differences between groups

Understanding Power

probability that statistics can detect relationships or differences that actually exist in the population studied (larger = more opportunity to appropriately accept or reject null hypothesis)

elem 1) alpha or level of significance (0.05)

power analysis

elem 2) standard power (0.80 80%)

power analysis

elem 3) effect size (strength of relationships)

power analysis

elem 4) sample size

power analysis

Refusal Rate

percentage of potential subjects who decide not to participate in a study

Refusal Rate = (# refused/#approached)x100

Attrition Rate

% of students dropping out of a study after sample size has been determined based on the sampling criteria (can occur when participants choose to drop out of a study or passively when they are lost to follow up)

Attrition rate = (#dropping out/#total sample size)x100

Independent Variable

a variable that influences another variable; also the variable that the researcher controls or manipulates to affect the dependent variable

Dependent Variable

an outcome variable that is affected or influenced by the independent variable

Research Question

what the research team is trying to answer through the study

Null Hypothesis (h0)

the hypothesis that suggests there will be no statistically significant effect on the variable(s) being studied - proved wrong “there is no difference, there is no association”

Alternate Hypothesis (H1 or Ha)

the hypothesis that observations from a sample are influences by a non random element; the hypothesis the researcher is interested in

Sampling method

process of selecting people, events, behaviors or other elements that are representative of the population being studied (study problem and purpose, population studied, expertise and experiences)

Quantitative Research

objective reproach methodology used to describe, explain relationships and determine the cause and effect interactions between variables (#s)

Qualitative studies

subjective and are conducted to describe and give meaning to life experiences, cultures or historical events

Mixed Methods Studies

used both quantitative and qualitative methods

Probability Sampling

• random sampling

• requires every member of study population has an equal and independent opportunity to be chosen for inclusion

Sampling Frame

each person or element in a study target population and then randomly selecting a sample from that population

Random Sampling ensures…

the representativeness of the sample, that the study has adequate power

Random assignment of study participants to groups…

design strategy to promote more equivalent groups at the beginning of the study and to reduce the potential for error

Prob: Simple Random Sampling

occurs trough a random selection of members from the sampling frame

can be accomplished in many ways but the most common is to utilize a computer generated program (computer puts you into random group)

Prob: Stratified Random Sampling

used when the researcher knows some of the variables within a population that will affect the representativeness of the sample

ex: age, gender, ethnicity, medical diagnosis

Prob: Cluster (Complex) Sampling

used in two situations: when the time and travel necessary to use simple random sampling would be prohibited, and when the specific elements of a population are unknown making it impossible to develop the sampling frame

• to conduct cluster, a list of all the states, cities, institutions or organizations associated with the elements of interest can be obtained - random selection then occurs

Prob: Systematic sampling

• requires ordered list of all the members of the population

• individuals are selected through a process that accepts every kth member on the list using a randomly selected starting point

• ex 1000 participants, sample of 100 is desired. k=1000/100=10, so every 10th person is invited to participate

Nonprob: nonrandom sampling

does not extend an equal opportunity for selection to all members of the study population never assume a probability sampling method was used in a study the research team should list it for you

Nonprob: convenience sampling

most frequently used

• enroll subjects who are accessible and available to participate in the study

• subjects are enrolled until target sample size obtained

• does not allow for the opportunity to control for sampling errors or biases

Nonprob: Quota Sampling

used to ensure adequate representation of all types of subjects who are likely to be underrepresented (i.e. women, elderly, minorities)

• used in conjunction w/ convenience sampling to help ensure inclusion of identified subject

• can be used to mimic the known characteristics of population

• improvement over convenience sampling because it decreases sampling error or bias

Nonprob: Purposive Sampling

occurs when the keashercer consciously selects subjects, elements, events or incidents to include in the study

• this sampling method can be a good way to explore new areas of study

• has been criticized because the researcher’s judgements in the selection of the cases cannot be evaluated or understood

Nonprob: Network/snowball sampling

makes use of social networks and the fact that the friend often have common characteristic

“friends of friends”

• useful for gathering hard to get samples, things that have not been previously identified for study or can help the researcher explore a particular area of interest

• sampling errors or biases are inherent with this method

Nonprob: Theoretical Sampling

used in the research process to advance the development of a theory and is more commonly used in grounded throw studies (don’t really worry about this one)

sampling or eligibility criteria

list of requirements or characteristics essential for membership in the target population

sampling inclusion criteria

requirements that must be present for inclusion into the sample (age range, gender, disease)

sampling exclusion criteria

requirements the if present eliminate or exclude participants from being induced in the sample (not in age range, not needed gender, does not have specific disease)