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Reliability and Validity |
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Psychology Research Methods (IV) |
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Reliability and
validity are essential to measurements and research procedure designs.
These two concepts are distinct yet related. While high reliability does
not warrant validity, a study cannot achieve validity without
reliability.
Reliability Reliability is the consistency of your measurement, or the degree to which an instrument measures the same way each time it is used under the same condition with the same subjects and the testing procedure is free from random errors of measurement. It asks the question: "Did we measure accurately?" For example, if you have a test consisted of math questions. The test and the testing procedure have to be able to yield consistent results on repeated trials in order to satisfy the reliability criterion. Validity Validity is how close what is being measured on the paper is to what we intend to measure in our theory. It eventually leads to how close our conclusion based on the measurement results is to the truth. It asks the question: "Did we measure what we were supposed to measure?" For example, suppose the above mentioned math test is intended to be part of an IQ test. Even if it is a highly reliable test, one can still ask the question: Are the math skills measured by this test really a component of the IQ? Or, does the test result reflect a person's IQ? Or, to which degree does a person's math score indicate his or her intelligence level? While high reliability does not warrant validity, a study cannot achieve validity without reliability. |
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Correlation and Causality |
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Psychology Research Methods (I) |
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Correlation In psychology, when two variables (e.g., self-esteem and popularity) are tested and determined to have a relationship, they are said to be "correlated". They can either be positively correlated, that is, the two variables increase and decrease at the same time. For example, when self-esteem increases, popularity increases at the same time. On the other hand, the relationship between two variables may also be identified as a negative correlation, which can be just as important as a positive correlation. Two variables are negatively correlated when one goes up while the other goes down, and vise versa. For example, when self-esteem increases the rate of teenage pregnancy decreases. Correlation coefficient, which can range from -1.00 to +1.00, is a measure of the direction and the strength of a correlation. Correlation between variables is established through correlational studies in social psychology. (See "Types of Psychology Research".) Causality Correlation simply means that the two factors occur at the same time. It does not say anything about their causal relationship (AKA cause-effect relationship) - which variable is the cause; which variable is the result. Using the self-esteem and popularity example, as far as causality is concerned, there are three possibilities: (1) high
self-esteem leads to popularity, Instead, both are the result of another factor or a group of other factors such as academic achievement and athleticism. Again, an established correlation between two factors does not necessarily indicate the direction of the cause-effect relationships or that a cause-effect relationship definitely exists. However, if a strong relationship is found between two variables, causality can be tested by using experimental studies. (See "Types of Psychology Research".) |
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Theory and Hypothesis |
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Psychology Research Methods (II) |
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A theory is a set of statements or principles devised to explain a phenomenon, especially if they have been repeatedly tested or have been widely accepted and can be used to make predictions about natural phenomena. A hypothesis is a tentative explanation for an observation, phenomenon, or scientific problem that can be tested by further investigation. Although in casual usage, the two terms are sometimes interchangeable, their differences in psychology research include the following:
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Types of Research |
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Psychology Research Methods (III) |
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There are two major types of psychology research: Correlational studies and Experimental studies. Each has a variety of different settings and controls. Correlational Studies Purposes: Correlational studies aim at identifying relationships between variables. There can be three kinds of turnouts: No relationship, positive correlation, and negative correlation.
Limitations: Correlation =/= Causal Relation As it turned out, two independent carefully conducted studies found that there is no causal relationship between these two factors. They are correlated because both of them are correlated to some other factors: intelligence and family social status. When these factors were controlled, the correlation between academic achievement and self-esteem disappeared. Be very careful about this. Another example, does college education lead to higher income? Or does socio-economic background lead to both college education and higher income? In order to study cause-effect relationship, we have to hold social-economic factors and all other factors constant. That can be done in experimental studies can. But not in correlational studies. Correlational studies may hint or suggest that one variable influences another, but they are never proof of causality. |
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Types of Research |
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Psychology Research Methods (III) |
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Types of Correlational Studies 1. Natural Observation Advantages:
Disadvantages:
Make an Observation More Scientific
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Types of Correlational Studies
2. Scientific Survey and Test
Random sampling:
Survey procedure in which every person in the population being studied has an equal chance of being chosen to be in the study.
Random sampling is key; number of people surveyed is not. No matter how large the population is, a survey only needs about 500 to reach a 95% confidence with plus or minus 5% accuracy. Opinion polls run by media often are not scientific no matter how many people have participated in their polling, because they are not random samples.
It is almost impossible to achieve true, absolute random sampling. There will always be under-represented parts of the population. For example, phone surveys would exclude people who do not own telephones.
Scientific Design of Questionnaires / Tests
Factors:
Advantages of the Survey Method
Disadvantages of the Survey Method
Types of Correlational Studies
3. Case Study
Advantages:
Disadvantage:
Types of Correlational Studies
4. Archive Research
Archive research is reviewing and analyzing records by previous researchers.
Advantages:
Disadvantage:
Causal Studies: Experiments
An experiment is used
to determine causal relationship between variables. An experiment is a cohort
(group of subjects) study in which the investigator manipulates the predictor
variable-otherwise called the treatment, program or intervention-and then
observes the outcome. Experiments can be conducted in real situations (Field
Experiments) or research labs (Lab Experiments). Experiments are conducted by
following the rules and
guidelines of the scientific method.
A. Manipulate the Independent Variable
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This is the factor that the researcher manipulates.
- The hypothesized causal factor. E.g., Antidepressant Medication: Yes or No.
- Participants are random assigned to groups based on the independent variable.
E.g., Group 1 gets antidepressant; Group 2 gets placebo.
- They are also called "experimental condition" and the "control condition".
B. Measure the Dependent Variable
- The variable being
measured. E.g., relief in depression symptoms.
- A result of the independent variable.
C. Random Sampling
- A systematic way of
recruiting experiment's participants, during which every person in the targeted
population has an equal chance of being chosen to be in the study.
- Random sampling helps us generalize our findings to a population.
D. Random Assignment
- Random assignment is
the process of assigning participants to the conditions of an experiment such
that all persons have the same chance of being in a given condition.
- Random assignment neutralizes factors other than the independent variable and
the dependent variable.
- Random assignment helps us infer cause and effect.
E.g., A random sample of people who suffer from depression is randomly assigned to two conditions: (a) Medication and (b) Placebo. Therefore, the two groups are equal in their socio-economic background, health, and looks. The only difference is in the independent variable -- in this case, medication condition: antidepressant or placebo. After both groups receive their pills for two weeks, the independent variable is measured.
E. Double-Blind Experiments
Double-blind experiments are the most objective kind of experiments, during which neither the experiment administrators nor the participants know who is receiving what experiment treatment. In the above example, each participant does not know if he or she is given the antidepressant or the placebo. Neither do the "experimenter's helpers", who dispense the pills and who measure the participants' symptoms.
F. Advantage of experiment
It can establish causation (i.e., cause-effect relationship) between variables
Science: Correlational vs. Experimental
Objectivity, reproducibility, measurements guided by theory, and bases for the development of new theory, which explains the research findings in a more general environment - these are some of the components of scientific methods of conducting psychology research.
In everyday language, the term "experiment" is used to refer to any scientific study. But in fact, nonexperimental does not mean nonscientific. As discussed before, through scientific design of the questions and random sampling of participants, correlational studies can be scientific, too. What correlational studies fall short in comparison with experimental studies is not that they can't be scientific; it is that they can't establish causality between the variables being investigated. But is that really a shortcoming. We, scientists and social scientists, as well as lay people, often favor the experimental method because there we can manipulate research conditions and we can make conclusions about cause and fact. We like doing those as we like to control and to explain why things happen. What we should also remember, however, correlational studies have the following advantages:
Reliability and validity are essential to measurements and research procedure designs. These two concepts are distinct yet related. While high reliability does not warrant validity, a study cannot achieve validity without reliability.
http://psychology.about.com/ (2002)