| ReCAPP
Research Glossary
A | B
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| G | H | I | J
| K | L | M |
N | O | P | Q
| R | S | T | U
| V | W | X | Y
| Z
A
Affect
To have an influence on. For example, nutrition affects our health.
Antecedent
A factor that precedes and is associated with
a specific outcome — but does not necessarily cause
the outcome. For example, living in a community with a high unemployment
rate is an antecedent of adolescent pregnancy.
ANOVA
Stands
for Analysis of Variables. A
test of the statistical significance
of the differences among the mean scores of two or
more groups on one or more variables.
Association
The relationship of the occurrence of two events, without evidence
that the first event being investigated actually causes
the second event. For example, malaria occurs in warm climates with proper
breeding conditions for certain types of mosquitoes. Those conditions
are in association with the spread of malaria. The actual cause
of malaria is the malaria parasite.
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B
BDI
Logic Model
BDI Logic Model stands for "Behavior-Determinants-Intervention"
logic model. Such models are diagrams that identify the causal relationships
among interventions, the determinants of behaviors,
the behaviors themselves, and one or more health goals. Because the process
for creating BDI logic models involves specifying first the health
goal, then the behaviors affecting that health goal, then the determinants
of those behaviors, and finally interventions that can markedly affect those
determinants, the "B" comes before the "D" which comes
before the "I" in the name. Bias
That quality of a measurement device that tends to result in a misrepresentation
of what is being measured in a particular direction. For example, the
questionnaire item "Don't you agree that the president is doing a
good job?" would be biased in that it would generally encourage
more favorable responses.
Bivariate
Analysis
Analyzing
the association between two variables. For example,
the bivariate analysis found that the variables of exposure
to second hand smoke and lung cancer are positively associated.
C
Case Control
Study
An experimental approach in research where two groups of subjects are
studied and compared: an experimental group
and a control group. Case
Study
An in-depth exploration of one particular case (situation or subject)
for the purpose of gaining depth of understanding into the issues being
investigated. For example, out of 30 in-depth interviews, one may be singled
out for a case study.
Causality
The
relation between a cause and its effects.
If the relation is high, we say the causality is high.
For instance, there is a high causality between having
unprotected intercourse with someone infected with Chlamydia and becoming
infected with Chlamydia.
Cause
Something that brings about a particular condition, result or effect.
For example, the malaria parasite causes malaria.
Chi-Square
Test
The chi-square test is performed to test whether two variables
can be considered statistically independent. When the chi-square
statistic is large (i.e. if its P-value
is less than a predetermined significance level such as 0.05), then the
null hypothesis of independence must be
rejected.
Cohort
A cohort is a group of beings (commonly people) who are surveyed
or studied over a period of time. Typically, data are collected from a
cohort at multiple points in time, such as before and after an
intervention.
Confidence
Level
The degree of certainty that a statistical
prediction is accurate. Generally, confidence level of 95% to 99% is considered
acceptable.
Continuous
Variable
A variable that can be expressed
by a large (sometimes infinite) number of score values. For example, height,
temperature, and grade point average are continuous variables.
Contrast with dichotomous variable.
Control
Group
A group of subjects to whom no experimental stimulus (e.g., a health
promotion program) is administered and who should resemble the experimental
group in all other respects. The comparison of the control group
and the experimental group at the end
of the experiment points to the effect of the experimental stimulus.
Correlation
A measure of association between two variables.
It measures how strongly the variables are related, or change, with each
other. If two variables tend to move up or down together, they are said
to be positively correlated. If they tend to move in opposite directions,
they are said to be negatively correlated.
Cost-Benefit
Analysis
The
process of assessing and comparing both the costs (financial cost, resources
needed, etc.) and the benefits of a course of action (such as an intervention
or a research study) in order to determine if it is a desired course of
action. For example, the cost-benefit analysis of the
condom dissemination program found the program to be cost efficient —
the cost of 75 cents per participating teen was far less than the cost
of otherwise expected unintended pregnancies.
Cross
Sectional Study
A study that is based on observations representing a single point
in time. Contrast with longitudinal study.
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D
Data
Information collected and organized for analysis or decision-making.
Deduction
The logical model in which specific expectations of hypotheses
are developed on the basis of general principles. For example, starting
from the principle that all college deans are mean people, you might anticipate
that your dean won't let you change courses. The anticipation would be
the result of deduction. Contrast with induction.
Dependent
Variable
That variable that is assumed to depend
on or be caused by another variable (called the independent
variable). For example, if you find that teen pregnancy is partly
a function of the amount of formal education received by teens, then teen
pregnancy is being treated as a dependent variable. Formal education
is the independent variable.
Determinants
Determinants (also called "behavioral determinants")
are the factors that have a causal influence on some outcome. For example,
"being in love" or "going with someone" are determinants
or factors that affect the initiation of sex among people, and both the
availability of alcohol and perceived peer norms about alcohol use are
determinants or factors that affect adolescent drinking. Determinants
can include both risk and protective
factors. Determinants differ slightly from antecedents.
Antecedents must be related to some outcome and must logically precede
that outcome, but they do not necessarily cause the outcome. In contrast,
determinants imply causality.
Dichotomous
Variable
A
categorical variable that can place subjects
into only two groups, such as male/female, alive/dead, or pass/fail.
Distal
Factors are considered more distal from an outcome if they are
logically more distant from that outcome. For example, community poverty
is a factor that affects teen pregnancy rates. However, community poverty
is conceptually quite distinct from teen pregnancy and is therefore considered
distal. In contrast, motivation to avoid pregnancy is also related
to teen pregnancy rates, but it is closer conceptually and is therefore
considered more proximal.
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E
Effect
Something brought about by a cause or agent —
a result. For example, slurred speech is a common effect of drinking
too much alcohol. Evidence-based
Programs
Programs are considered evidence-based if there exists good evidence
that they have a positive impact on the outcomes that they are designed
to change. For example, some sex and HIV education programs are considered
evidence-based because their impact on sexual or contraceptive behavior
have been carefully measured with experimental designs, and these studies
produced strong evidence that the programs actually changed behavior in
a desirable direction.
Experimental
Design
A research design to investigate cause and effect
relationships between interventions and outcomes. Experimental designs
are case controlled studies which use
random sampling practices to place subjects
in control groups and experimental
groups and then compare the differences in outcomes.
Experimental
Group
A group of subjects to whom an experimental stimulus (e.g., a health
education program) is administered and who should resemble the control
group in all other respects. The comparison of the control
group and the experimental group (also called the "treatment
group") at the end of the experiment points to the effect
of the experimental stimulus.
Exploratory
Research
Research
that looks for patterns, ideas, or hypotheses
rather than try to test or confirm hypotheses. For example, one exploratory
research project interviewed 100 adoptive parents to learn what
their common struggles and issues were in raising adoptive children.
Exponential
Power
The number of times
a number is multiplied by itself, usually written as an exponent. For
example, 83 is 8 to the third power and means 8X8X8=512.
External
Validity
The extent to which the findings of a study are relevant
to subjects and settings beyond those in the study. Another term for generalizability.
Contrast with internal validity.
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F
Fidelity
In intervention research, fidelity commonly refers to the extent
to which an intervention is implemented as intended by the designers of
the intervention. Thus, fidelity refers not only to whether or not
all the intervention components and activities were actually implemented,
but whether they were implemented in the proper manner.
Field
Notes
A written/typed record of events and observations kept
by a researcher. For example, a child development researcher might keep
field notes as she observes toddlers interacting in a
play group.
Focus
Group
A qualitative research technique in which an experienced
moderator leads a group of respondents (usually 8-12 persons) through
an informal discussion of a selected problem or issue, allowing group
members to talk freely about their thoughts, opinions, feelings, attitudes,
and misconceptions about the issue.
Formative
Research
Formative research (also called "formative evaluation")
is research that is conducted for the primary purpose of improving the
quality of the intervention. This may be in contrast to research that
is conducted to determine how an intervention was implemented (process
evaluation) or whether the intervention had intended effects (outcome
evaluation). Because formative research is designed to improve
the intervention, it is often conducted during the development of an intervention
and during the first few years of implementation.
Frequency
The number of occurrences of a specified event within a given interval.
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G
Generalizability
The extent to which research findings can be applied to more than the
specific observations upon which they are based. Sometimes this involves
the generalization of findings from a sample to a population.
H
Health Behavior
Health behavior refers to any type of behavior that has an impact
on the health of the beings involved. For example, avoiding sex or always
using contraception are health behaviors that affect the health goal
of avoiding unintended pregnancy. Hypothesis
A prediction of a relationship between one or more factors; a problem
under study, which can be tested. An example of a hypothesis is:
"If an adolescent girl has an older sister who gets pregnant as a
teen, she is more likely to get pregnant."
Hypothesis
Testing
The
classical approach to assessing the statistical
significance of findings. Basically it involves comparing observed
sample findings with theoretically expected findings (the hypothesis).
This comparison allows one to compute the probability that the observed
outcome could have been due to chance alone. The comparison also determines
if a null hypothesis is correct.
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I
Incidence
The number of new cases of a defined condition that occur during a specified
period of time in a defined population. Contrast with prevalence.
Independent
Variable
An
independent variable is presumed to cause or determine a dependent
variable. For example, if we discover that dancing ability is partly a
function of hours of dance class, then "hours of dance class"
is the independent variable, and dancing ability is the dependent
variable. Note that any given variable might be treated as independent
in one part of an analysis and dependent in another part of an analysis.
Dancing ability might become an independent variable in the explanation
of cardiovascular health.
Induction
The logical model in which general principles are developed from specific
observations. See also deduction.
Internal
Validity
The extent
to which the results of a study can be attributed to the treatment, rather
than flaws in the research design. In other words, the degree to which
one can draw valid conclusions about the causal effects of one variable
on another. Contrast with external validity.
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L
Level of Significance
More
fully the level of statistical significance.
The probability (abbreviated "p") that a result
would be produced by chance (sampling or random error). The lower the p,
the less likely chance or errors occurred, and the more likely the finding
is statistically significant.
Likert Scale
A type of response format used in surveys developed
by Rensis Likert. Likert items have responses on a continuum and response
categories such as "strongly agree," "agree," "disagree,"
and "strongly disagree."
Linear
Relationship
A relationship between two variables that
can be described by a straight line when variable values are plotted on
a graph. The more the plotted points tend to fall along a straight line,
the stronger the linear relationship.
Logistic
Regression Analysis
A kind of regression analysis commonly
used when the dependent variable is dichotomous (e.g., "yes"
and "no" scored 0 or 1). This type of analysis is useful to
predict whether something will happen or not (e.g., had sex or used contraception).
Longitudinal
Study
A study design involving the collection of data at different points
in time (i.e., three months, six months and 12 months after an intervention).
Contrast with cross sectional study.
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M
Matching
A research design in which subjects are matched on characteristics
that might affect their reaction to a treatment. For example, once pairs
of matched subjects are determined, one member of each pair is assigned
to a group receiving treatment (experimental
group), and the other is assigned to the control
group and does not receive treatment. A study that uses random assignment
to place its subjects is considered more rigorous than a study that uses
matching.
Mean
An average, computed by totaling the values of several observations
and dividing by the number of observations. For example, if the ages of
five men are 16, 17, 20, 54, and 88, the mean age of the men would
be 39. Compare to median and mode.
Median
A measure of central tendency representing the value of the "middle"
case in a rank-ordered set of observations. For example, if the ages of
five men are 16, 17, 20, 54, and 88, the median age would be 20.
Compare to mean and mode.
Mediating Outcomes
Mediating outcomes are the effects of an intervention that, in
turn, have an impact upon other even more important phenomena. For example,
an HIV education program may increase knowledge and change values about
early initiation of sex (mediating outcomes), effects which, in
turn, lead to a delay in the initiation of sex.
Meta-Analysis
The combining of data from several different research studies to gain
a better overview of a topic than what was available in any single investigation.
Data obtained from combined studies must be comparable in order to be
evaluated by this method.
Mode
A measure of central tendency representing the most frequently observed
value or attribute. For example, if the ages of five adolescents are 16,
17, 17, 18, and 19, the mode age would be 17. Compare to mean
and median.
Multivariate Analysis
The analysis of simultaneous relationships among several variables.
Examining simultaneously the effects of age, sex, and social class on
sexual debut would be an example of multivariate analysis.
Mutually Exclusive
Describing
two events, conditions, or variables which cannot
occur at once. For example, subjects in a study cannot be both female
and male, HIV positive and HIV negative, pregnant and not pregnant, for
those are mutually exclusive categories. They could,
however, be both female and HIV positive because those are not mutually
exclusive.
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N
Needs Assessment
A process
of identifying problems and needs in a target population to make decisions,
set priorities, set objectives, and explore alternative approaches or methods
to aid in the planning and implementation of programs. Needs assessments
can be conducted using a variety of tools including surveys,
interviews and focus groups.
Null
Hypothesis
The null hypothesis represents a theory that has been put forward,
whether because it is believed to be true or because it is to be used
as the basis of argument, but has not been proved. For example, in a clinical
trial of a new drug, the null hypothesis might be that the new
drug is no better, on average, than the current drug.
O
Objectivity
The
quality of relating to facts or conditions without distortion by personal
feelings, prejudices, or interpretations. Objectivity is
an extremely important quality for researchers to possess. Objectivity
allows researchers to make conclusions based on the data which may directly
oppose their own personal beliefs.
Odds Ratio
The odds ratio is a measure of association in which a value of
"1.0" means that there is no relationship between variables. The value
of an odds ratio can be less than or greater than 1.0. The size
of any relationship is measured by the difference (in either direction)
from 1.0. An odds ratio less than 1.0 indicates an inverse or negative
association. An odds ratio greater than 1.0 indicates a positive
relation.
Operational
Definition
A
description or set of criteria for defining a variable
or condition with objectivity. For example,
the operational definition of an obese person could be
one who weighs more than 120% of his or her "ideal weight" as defined
by an insurance company chart.
Outcome
Evaluation
Outcome evaluation is a type of evaluation that measures the effects
of an intervention. Typically, the emphasis is on the measurement of desired
intended effects, but sometimes the impact on possible negative effects
is also measured. Outcome evaluation is in contrast to formative
research or process evaluation. Sometimes,
but not always, people distinguish "impact evaluation," which
measures effects on short-term mediators from outcome evaluation,
which measures effects on longer term health goals.
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P
Participatory
Research
A collaborative approach to conducting research or program evaluations
where the research process is controlled by the people in the program or
community — not solely the professional researchers. The purpose of
this type of shared inquiry is to educate the people involved in the program
and improve the nature of the practice being studied. Participatory research
has been used with great success in schools and in international programs.
P-Value
The P-value, or probability value, of a statistical hypothesis
test (e.g., chi-square test) is the probability
of getting a value of the test statistic as extreme as or more extreme
than that observed by chance alone, if the null
hypothesis is true. Small p-values suggest that the null hypothesis
is unlikely to be true. The smaller the p-value, the more convincing
the rejection of the null hypothesis.
Percentage
The number of units with a certain characteristic divided by the total
number of units in the sample and multiplied by 100. For example, the
percentage that represents five out of 20 boys is 5 divided by
20 x 100, which is 25%.
Population
(N)
A
group of persons (or institutions, events or other subjects of study)
that one wishes to describe or wishes to generalize about. The number
of members in the population is generally referred to
as N. In contrast, n generally refers to a sample of the
population.
Pretest/Posttest
A
pretest is a test given (or measurement taken) before
an experimental treatment begins. A posttest is given
after the experimental treatment. By contrasting the results of the pretest
with those of the posttest, researchers gain evidence
about the effects of the treatment.
Prevalence
The total number of cases of a defined condition present in a specific
population at a given time. Contrast with incidence.
Probability
A probability provides a quantitative description of the likely
occurrence of a particular event. Probability is conventionally
expressed on a scale of zero to one. A rare event has a probability
close to zero. A very common event has a probability close to one. The
probability of drawing a spade from a pack of 52 well-shuffled
playing cards is 13 spades divided by 52 cards, or .25.
Probability Sample
Random selection procedures to ensure that each unit of the sample
is chosen on the basis of chance. All units of the study population should
have an equal or at least a known chance of being included in the sample.
Probing Questions
Prompts
used during interviews to assist respondents in answering the interview
questions. For example, when asked what he liked about being a health
educator, the respondent said, "I like feeling like I help people." The
interviewer used the follow-up probing question, "How
do you think you have helped people as a health educator?" to get a more
specific response.
Process
Evaluation
Process evaluation is a type of evaluation that measures the implementation
of an intervention. For example, it may assess the extent to which the
components and activities of an intervention were actually implemented,
the qualities of the implementation, the number of people who participated,
and participants' reaction to the intervention.
Proportion
The ratio of the number of cases possessing a property (numerator)
to the total number of cases observed (denominator). For example, if 5
out of 20 girls participated in a workshop, the proportion of girls
participating in the workshop is 5 divided by 20, which is .25.
Protective
Factor
Any factor whose presence is associated with an increased protection
from a disease or condition. For example, good school performance is a
protective factor against adolescent pregnancy.
Proximal
Factors are considered more proximal to an outcome if they are
logically closer to that outcome. Compare to distal.
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Q
Qualitative Analysis
The examination and interpretation of non-numerical observations for
the purpose of discovering underlying meanings and patterns of relationships.
For example, analyzing training participants' written comments on how a
training could be improved is a form of qualitative analysis.
Quantitative Analysis
The numerical representation and manipulation of observations for
the purpose of describing and explaining the phenomena that those observations
reflect. For example, analyzing training participants' ratings (between
one and five) of the overall training is a form of quantitative analysis.
Quasi Experimental
Design
Quasi experimental design is similar to experimental
design, but does not include the random assignment of subjects. The
quasi experimental design is, therefore, not as strong, and it's
much harder to establish causal relationships between
events and conditions.
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R
Random
Sampling
A sampling technique in which a group of subjects is selected for a
study from a larger group (population). Each individual is chosen entirely
by chance, and each member of the population has a known, but possibly non-equal,
chance of being included in the sample. By using random sampling,
the likelihood of bias is reduced and true experimental
design can be achieved. Rate
The quantity, amount or degree of something being measured in a specific
period of time. An example of a rate is the teen pregnancy rate
which is usually expressed in the number of pregnant teens per 10,000
teens within one year's time.
Ratio
Numerical expression which indicates the relationship in quantity,
amount or size. For example, in a class with one teacher and 15 students,
the teacher to student ratio is one to 15.
Regression
Analysis
A
data analysis approach that is used to predict one variable by knowing
one or more other variables. Regression analysis is used to answer
such questions as "How well can I predict the values of one variable,
such as frequency of sex (Y), by knowing the values of another variable,
such as attitudes about sex and/or having and older boyfriend/girlfriend
(X)."
Relative
Risk
The risk of getting a disease in a group with the risk factor divided
by the risk of getting a disease in a group without the risk factor.
Reliability
The quality of measurement method that suggests that the same data
would have been collected each time in repeated observations of the same
phenomenon. In the context of a survey, we would expect that the question
"Did you attend church last week?" would have higher reliability
than the question "About how many times have you attended church
in your life?" Compare with validity.
Response Rate
The
percentage of responses received to a particular survey,
question, or other measurement tool. For example, if 100 surveys were
mailed out and 80 surveys were completed and returned, the response
rate for the survey would be 80%. If only 40 out of the 80 respondents
answered question five, the response rate for question
five would be 50%.
Rigorous Research
Research is considered rigorous if the methods of the research
study are designed and implemented so that very strong evidence is produced
to substantiate the study's conclusions. For example, a study would probably
be considered rigorous if it employed an experimental design with
random assignment and measurement of possible outcomes both before (pretest
survey) and well after (post-test or follow-up survey), had a large sample
size, measured outcomes reliably, and was conducted with proper statistical
analyses.
Risk
Factor
Any factor whose presence is associated with an increased risk of
a disease or condition. For example, prior history of sexual abuse is
a risk factor for adolescent pregnancy.
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S
Sampling
The selection of a number of study subjects from a defined study population.
Secondary
Analysis
A
type of research in which data collected by others
are reanalyzed. For example, Dr. More is using data from the three West
Coast studies on sexually transmitted disease incidence in youth to study
trends in syphilis incidence in California.
Snowball Sample
A non-probability sampling method often employed in field research.
In snowball sampling, each person interviewed may be asked to suggest
additional people for interviewing.
Standard
Deviation
A measure of the spread or dispersion of a set of data. The more widely
the values are spread out, the larger the standard deviation. For
example, given two separate lists of exam results from a class of 30 students
in which one list ranges from 31% to 98% and the other from 82% to 93%,
then the standard deviation would be larger for the results of the first
exam. Standard deviation is calculated by taking the square
root of the variance.
Statistic
A quantity that is calculated from a sample of data. It is used to
give information about unknown values in the corresponding population.
For example, the average of the data in a sample is a statistic
used to give information about the overall average in the population from
which the sample was drawn.
Statistical
Power
A
gauge of the sensitivity of a statistical test, that is, its ability to
detect relationships. Specifically, the probability
of rejecting a null hypothesis when it is
false — and therefore should be rejected. In general, the statistical
power increases with your sample size. Also called "Power"
or a "Test."
Statistical
Significance
A general term referring to the unlikeliness that relationships observed
in a sample could be attributed to sampling error alone. It is customary
to describe one's finding as statistically significant when the
obtained result is among those that, theoretically, would occur no more
than five out of 100 times when the only factors operating are the chance
variations that occur whenever random samples
are drawn.
Survey
A questionnaire type tool generally used to gather standardized information
from a group of subjects.
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T
Theory
A statement or set of statements designed to explain a phenomenon
or class of phenomena. For example, Social Learning Theory describes
how human behavior is a product of environmental, social and personal
factors.
Triangulation
Using
more than one method to study the same thing. For example, if you were
interested in people's attitudes toward environmental issues, you could
look at patterns of voting behaviors for environmental candidates and
issues; or you could interview leaders of the Sierra Club, the Nature
Conservancy, and similar groups; or you could conduct a survey
of a representative sample of the entire population.
Or you could do all three and put the results together, in which case
you could say that you had used a research strategy of triangulation.
T-test
A statistical test to determine whether the difference between two sample
means is statistically significant.
Type
I Error
In a hypothesis test, a Type I error occurs when the null
hypothesis is rejected when it is, in fact, true. That is, it is wrongly
rejected. For example, in a clinical trial of a new drug, the null hypothesis
might be that the new drug is no better, on average, than the current
drug. A Type I error would occur if a conclusion was made that
the two drugs produced different effects when, in fact, there was no difference
between them. A Type I error is often considered to be more serious,
and therefore more important to avoid than a Type
II error.
Type
II Error
In a hypothesis test, a Type II error occurs when the null
hypothesis is not rejected when it is, in fact, false. For example,
in a clinical trial of a new drug, the null hypothesis might be that the
new drug is no better, on average, than the current drug. A Type II
error would occur if it were concluded that the two drugs produced
the same effect when, in fact, they produced different ones. Contrast
with Type I error.
Typology
The study of or analysis or classification
based on types.
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V
Validity
The quality of a measurement tool that suggests the tool accurately
reflects the concept that it is intended to measure. For example, your IQ
would seem a more valid measure of your intelligence than
would the number of hours you spend in the library. It is important to realize
that the ultimate validity of a measure can never be proven. Compare
to reliability. Variables
Logical groupings of attributes. For example, the variable
"gender" is made up of the attributes "male" and "female."
Variance
The measure of the "spread" of a distribution of random
variables (or observations) about its average
value. The larger the variance, the more scattered the observations on
average. Taking the square root of the variance produces the standard
deviation.
W
Weighted
Data
Any information given
different weight in calculations. For example, a final examination counts
twice as much as (is weighted double) the midterm.
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This
glossary was developed with contributions from the following resources:
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