Quantitative Design
- what process
- involves
- vehicle for
- what kind of analysis
Systematic scientific process of testing relationships, differences, and cause-and-effect interactions among and between variables
Involves a plan, a structure, and a strategy
Vehicle for hypothesis testing or answering research questions
Statistical analysis of numerical data
Variables in Quantitative Design
-Name the 3 variables and describe them
Dependent variable
-Outcome variable, observed but not manipulated
Independent variable
-Presumed effect variable manipulated in experimental studies
Extraneous variables
-Variables that may interfere with the results being studied
(age, gender, natural occurring event, researcher in the room)
Importance of Control 4
Hold conditions of the study constant
Avoid bias
Specific sampling and data collection criteria
E.g., Controlling extraneous variables
- Homogeneous samples
- Consistent data-collection procedures
- Manipulation of IV
- Randomization
Types of Validity 2 and describe them
Internal Validity
-Researcher controls all extraneous variables and the only variable influencing the results of a study is the one being manipulated by the researcher
External Validity
- The extent to which the results of a study can be generalized or extended to other populations or environmental conditions
- How well did they control these things, how well can they apply it to others
6 Threats to Internal Validity and describe them
History
-Another specific event may affect the DV (dependent variable/outcome) [anything can happen]
Maturation
-Potential changes in an individual as a function of time (Threat to studies over a time)
Testing
-Repeated testing may influence participants’ responses (pre test / post test)
Instrumentation
Changes in how variables are measured or observed (biggest threat) [are you using the same tool, validity/reliability]
Mortality
loss or attrition of participants
Selection bias
The way in which participants are chosen and grouped. Do pretreatment differences exist?
3 Threats to External Validity
Selection Effects
Concerns about generalizability, when an ideal sample cannot be attained
Reactive Effects
Hawthorne effect; changes in participants’ behaviour as a response to being studied
Measurement Effects
Use of a pre-test allows participants to examine their attitudes and responses for follow-up testing
Types of Quantitative Designs 3 and describe them
Experimental Designs
-manipulation of independent variables, randomization, control of extraneous variables, cause and effect
Quasi-Experimental Designs -manipulation, naturally occurring comparison groups, statistical control of extraneous variables Non-Experimental Designs -Naturally occurring variation in independent variables, statistical grouping, statistical control of extraneous variables
Experimental Design
cause and effect requires what three things (causation)
Causal variable and effect variable must be associated with each other
Cause must precede the effect
Relationship must not be explainable by another variable
Randomized Clinical Trials (RCT) 4
drug studies!
Pre-test Post-test Control Group Design
Considered “gold standard” regarding cause-and-effect relationships
Minimal bias is introduced
Same results over and over?
Quasi-Experimental Design
Main difference?
Pros 3
Main difference: They usually lack the element of randomization and/or may lack a control group
-natural groups, everybody is in experimental/ treatment group
- Practical, feasible and the results are generalizable
- More adaptable to real world settings than controlled experimental designs
- May be the only way to evaluate the effect of the independent variable on the variable of interest
Non-experimental Design 6
5 types
- To examine events, people, situations as they naturally occur
- Test relationships and differences among variables of interest
- Requires clear, concise research problem or hypotheses based on theory
- Elements of control are not possible
- looking for natural change
- no provided intervention
Survey research
-Descriptive, Exploratory, Comparative
Relationship/Difference Studies
- Correlational
- Developmental
- Cross-Sectional
- Longitudinal or Prospective
- Retrospective or Ex Post Facto
psychometric Research
Secondary Analysis
Epidemiological Studies
Survey research 5
2 advantages
4 disadvantages
Detailed descriptions of existing variables collected through a questionnaire or interview
Small or large samples of participants recruited from defined populations
Data used to justify and assess current conditions and practices or to improve health care practices
Descriptive, exploratory or comparative (terms used alone, interchangeably, or together to describe design)
Relationships and differences, NOT causation since u cant control all the elements so you cant says cause and effect
- A great amount of information can be obtained from a large population in a more economical manner with very accurate information
- if a sample is representative of population a relatively small number of participants can accurately represent the views of the population
- Information may be superficial
- Breadth rather than depth is emphasized
- Great deal of research expertise is required
- Large scale studies can be expensive and time consuming
Relationship/Difference Studies:
Correlational Studies: what is it
advantages:
disadvantages
2 Correlational Studies may be:
Correlational Studies:
The investigator examines a relationship between two or more variables (correlation)
Advantages: Flexibility, Large amount of data about the relationship, Potential for clinical application, Foundation for future studies, Explore relationship between variables that cannot be manipulated
Disadvantages Correlational:
Inability to manipulate variables of interest
No randomization in the sampling procedures (deals with pre-existing groups)
Researcher cannot determine a casual relationship between the variables
- Descriptive correlational where the goal is to describe the relationship between variables
- Predictive correlational where several variables are examined to see which are related and if the presence or absence of particular variables predicts a certain outcome
Relationship/Difference Studies
Developmental Studies:
Cross-Sectional 3
- Cross-sectional studies examine data at one point in time, from a number of subjects
- Cohort studies can be cross-sectional if data is gathered from different cohort groups at about the same time
- Cross-sectional studies can explore relationships and correlations, differences and comparisons or both
Relationship/Difference Studies Developmental Studies: Longitudinal2 3 advantages 3 disadvantages
- AKA prospective or repeated-measures study
- Collect data from the same sample at different points in time
Advantages:
- Each participant acts as his/her own control
- Increased depth of responses
- Early trends can be analyzed
Disadvantages:
-Data collection may take a long time, increasing costs in time, effort, and money
Testing effects may be a threat
mortality is a significant threat owing to the increased potential for attrition
Relationship/Difference Studies 4 Developmental Studies: Retrospective advantages 2 disadvantage 3
used when looking at harmful things because you cant make people do harmful things
- AKA ex post facto “from after the fact”
- Researcher attempts to link current events to past events
- DV has already been affected by the IV
- E.g., Hypothesis variable X (cigarette smoking) is related to and a determinant of variable Y (lung cancer)
Advantages:
- Similar to the advantages of the correlational design
- Offers a higher level of control
Disadvantages:
- Unable to draw a causal link between two variables
- Alternate hypothesis may be the reason for the documented relationship
- Difficulty finding similar group members
Psychometric research 3
Involves 4 things in this exact order
- Development and evaluation of data collection instruments, scales and techniques
- Psychometric concerned with measurement of a concept with reliable and valid tools
- Researcher interested in identifying intangible concepts (constructs) and making them tangible by developing an accurate measurement tool
Involves the following in the order of:
- Defining the construct or concept to be measured
- Formulating the tool’s items
- Developing instructions for users and respondents
- Testing tool’s reliability and validity
Secondary Analysis3
Previously collected data from one study are reanalyzed for a secondary purpose
May involve a subset of a specific group of people or geographical setting
Exploring specific variables in greater detail through statistical analyses
Epidemiological Studies 3
What are the two types conducted
Examine factors affecting the health and illness of populations
Often in relation to the environment
Distribution, determinants, and dynamics of health and disease
Prevalence- number of people affected
reduced by cured, die
-meds that prevent death increase prevalence (not necessarily bad)
-Prev is Incidence multiplied by duration of disease
Incidence- number of cases occurring in a particular period of time
-
Class 122
-
Class 2 Penz material30
-
Class 2 PICO, Searching CINAHL and APA Citation14
-
Class 310
-
Class 419
-
Class 719
-
Class 819
-
Class 8 Penz, K. & Duggleby, W. (2011).12
-
Class 912
-
Class 9 Eley, Eley, Bertello, & Rogers-Clark (2012). Why did I become a nurse? Personality traits and reasons for entering nursing.13
-
Class 11 CADTH7
