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The investigation of the distribution and determinants of disease within opulations or cohorts.
Study conducted by examining a single phenomenon across multiple populations at a single point in time with no intent for followup in the design.
Study conducted by following subjects over a period of time, with data collection occurring at prescribed intervals.
The meticulous descriptive exploration of a single unit of study such as a person, family group, commnunity, or other entity.
An investigation using a single case or subject in which baseline data are collected, an intervention is applied, and the reponses are tracked over time.
Single subject designs that continue to measure the response of the individual as the intervention is withdrawn or withdrawn and reinitiated.
Designs that involve the analysis of two variables to describe the strength and direction of the relationship between them.
Research designed to search for variables measured at one point in time that may forecaset an outcome that is measured at a different point in time.
Tests of association used to determine whether a set of relationships fits in the real world in the way the relationships are hypothesized in the researcher's model of reality.
Tests of model fit
A variable that is not measured but is related to each variable in the relationship and may affect the correlation of the data.
A condition in which two variables have an appearance of causality where none exists. This link is invalid when objectively examined.
Descriptive research illuminates an understanding of what is.
Numbers in a data set that are collected to represent research variables.
The initial step in descriptive analysis is to choose the appropriate statistical analysis for the level of measurement of each variable.
Descriptive questions are designed to describe what is going on or what exists
Cohort studies examine the following variables:
- Patterns of change
- Growth or trends over time
Strengths of cross sectional studies:
- Practical and economical
- No waiting for the outcome
Limitations of cross sectional studies
- Do not capture changes that occur
- Impractical for the study of rare diseases or uncommon problems
The purpose of studying single subjects is to assess individuals, with the expectation of generalizing to other individuals in similar situations or conditions.
A case study is not intended to represent a population but to test theory or demonstrate the effectiveness of a practice from a unique and individual perspective
Strengths of case studies:
- Provide indepth info
- Changes over time observed
Limitations of case studies:
- No baseline measurement to provide comparison with the intervention outcome
- difficult to determine whether there is an improvement in outcome becuase causation cannot be inferred
- Interpretation can be biased
- Results cannot be generalized
Strengths of single subject studies
- useful in exploring behavioral responses
- Explore real changes
- easier to implement
Limitatinos of single subject studies
- not generalizable
- not considered sufficient evidence for a practice change
Strengths of correlation studies:
- Relatively uncomplicated to plan and implement
- Researcher flexibility
- Outcomes have practial application in practice
Limitationsof correlation studies
- Cannot manipulate variables of interest so causality cannot be est.
- Designs lack control and randomization so rival explanations may be posed for relationships
- Suppressor variable--the corelation that is measured may be the result of a suppressor variable-one that is not measured but is related to each varaible in the relationship