Chapter 9: Multivariate Correlational Research

Question 1

Multivariate Designs

Answer 1

• (such as longitudinal and multiple regression designs) involve more than two measured variables
• Help establish causality or get closer to causality
• They are extremely useful and widely used tools, especially when experiments are impossible to run

Three criterai for establishing causation:
1. Covariance
2. Temporal Precedence
3. Internal Validity

Question 2

Longitudinal Designs

Answer 2

• Where you are collecting data from the same group over time
• May collect causality
• Measuing the same varibales in the same poepl at several points in time
• Adapted to test causal claims

Question 3

Cross Sectional Correlations

Answer 3

• Cannot establish temperal precedence
• They test to see whether two bariables, measured the same point in time

Question 4

Autocorrelations

Answer 4

• Where you looking at the correlation between each variable within each self at one point
• Need to see for consistency, how stable the variables are
• Cannot establish temporal precedence

Question 5

Cross - Lag Correlations

Answer 5

• Can closer to establish temporal precedence
• The only way to be confident is by conducting a study. Looking at behavior
• Look at correlation at one variable at pine point and look at another variable at one pine point
• If one of the pine is successful, it is neutral refurbishing - Can know what is causing it

Which shows whether the earlier measure of one variable is associated with the later measure of the other variable
Address the directionality problem and help establish temporal precedence

Question 6

Longitudinal Designs with Covariance

Answer 6

When two variables are significantlly correlated, there is covariance

Question 7

Longitudinal Designs with Temporal Precedence

Answer 7

• By comparing the relative strength of the two cross - lag correlations, the researchers can see which path is stronger
• If only one of them is statistically significant, the researchers move a little closer to determining which variable comes first. Therbye causing the other

Question 8

Longitudinal Designs with Internal Validity

Answer 8

• Longitudinal studies do not help rule of third variables
• Can’t be that certain

Question 9

Multiple Regression

Answer 9

• It can help us rule the third varible; thereby addressing some internal valdidity concerns
• You can try to predict another variable
• Control porsisble confounding variables

Question 10

“Control for”

Answer 10

• By conducting a multivariate design, researchers can evaluate whether a relationship between two key variables still holds when they control for another variable
• Statistically accurate way,It is considered the proportions of variability
• Easier way is to recognize that testing a third variable with multiple regression is similar to identify subgroups

Question 11

Criterion Variables

Answer 11

• The first step is to choose the variable they are most interested in understanding or predicting
• It is almost always specified in either the top row or the title of a regression table
• Dependent variable

Question 12

Predictor Variables

Answer 12

• Independent variable
• The rest of the variables measured in a regression analysis

Question 13

Beta

Answer 13

• There will be one beta values for each predictor variable
• Similar to r, in a way that they denotes the direction and strength of a relationship
• The higher beta is, the stronger the relationship is between that predictor variable and the criterion variable
• The smaller beta is, the weaker the relationship
• Unlike r, there are no quick guidelines for beta to india effect sizes that are weak, moderate or strong
• Due to beta changing, depending on what other predictor variables are being used - being controlled for - in the regression
• When p is less than .05, the beta is considered statistically significant
• When p is greater than .05, the beta is considered not significant, meaning we cannot conclude beta is different from zero

Question 14

Adding More Predictors to a Regression

Answer 14

• There are multiple other possible third variables
• Even when there are many more predictor variables in the table, beta still means the same thing
• Adding several predictors to a regression analysis can help answer two kinds of questions
  1. First: helps control for several third variables at once
  2. Second: by looking at the beta for all the other predictor variables, we can get a sense of which factors most strongly predict the dependent variable (ex: the chance of pregnancy)

Question 15

Regression in Popular Press Articles

Answer 15

• “Controlled for”
• “Taking into account”
• “Correcting for”
• “Adjusting for”

Question 16

Regression Does Not Establish Caustions

Answer 16

• Multiple regression in not a foolproof way to rule out all kinds of third variables
• Even though, multivariate designs analyzed with regression statistics can control for third variables, they are not always able to establish temporal precedence
• Even though multiple regression controls for any third variable the researchers do measure in the study, some other variable they did not consider could account for the association

Question 17

Getting Causality with Patten and Parsimony

Answer 17

• More patterns = more confidence of the results
• Approach can be called “pattern and parsimony” because there’s a pattern of results best explained by a single, parsimonious causal theory
• Parsimony is the degrees to which a scientific theory provides the simplest explanation of some phenomenon. Means the simplest explanation of a pattern of data - the theory that requires making the fewest exceptions of qualifications

Question 18

Mediators

Answer 18

• Variables that explains in which one variable effects the other
• It can be more complex
• You ask the how questions (how something happens)
• Why are two variables related?

Question 19

Mediators vs Third Variables

Answer 19

Similarities
- Both involve multivariate research designs
- Both can be detected using multiple regression

Differences
- Third variables are external to the bivariate correlation (problematic)
- Mediators are internal to the causal variables (not problematic)

Question 20

Moderators

Answer 20

• Ask for “whom” or “when”
• Are there certain groups of situations for which the two variables are more stongly related