Correlational Research Strategies
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Questions and Answers

Socioeconomic status has no influence on bathing rates and eating patterns.

False (B)

What are the three types of correlations discussed in the content?

Cross-sectional correlations, lag cross-correlations, autocorrelations

The term used for when a variable at an earlier timepoint is associated with another variable at a later timepoint is called __________.

lag cross-correlation

Match the following types of correlations with their descriptions:

<p>Cross-sectional correlations = Measure relationships at the same timepoint Lag cross-correlations = Measure relationships over time Autocorrelations = Measure relationships of a variable with itself over time</p> Signup and view all the answers

Autocorrelations measure how one variable relates to itself over time.

<p>True (A)</p> Signup and view all the answers

In the context of child language learning, what does 'temporal precedence' refer to?

<p>The parent's talk at an earlier time influences the child's movement later.</p> Signup and view all the answers

What does a correlation coefficient (r) of +1.0 indicate?

<p>A perfect positive correlation (D)</p> Signup and view all the answers

In a scatterplot, if points are widely spread out, it indicates a strong correlation.

<p>False (B)</p> Signup and view all the answers

Define a monotonic relationship in the context of correlation.

<p>A relationship where one variable consistently increases or decreases with another variable.</p> Signup and view all the answers

Spearman's correlation is used for examining the strength and direction of the ______ relationship between two variables.

<p>monotonic</p> Signup and view all the answers

Match the following correlation types with their appropriate usage:

<p>Pearson r = Used when variables are on a ratio or interval scale Spearman rho = Used when one or more variables are ordinal Linear correlation = Consistent change in one variable with change in another Nonlinear correlation = Inconsistent change between variables</p> Signup and view all the answers

Which statement correctly describes the assumption of independence in a correlational study?

<p>No two data points can come from the same individual. (D)</p> Signup and view all the answers

The closer the data points are to the regression line, the weaker the correlation between the variables.

<p>False (B)</p> Signup and view all the answers

In the context of correlational strategies, what variable is usually represented on the x-axis of a scatterplot?

<p>Independent variable</p> Signup and view all the answers

A ______ indicates the strength and direction of the correlation between two variables and ranges from -1.0 to +1.0.

<p>correlation coefficient</p> Signup and view all the answers

Which of the following is an example of a non-linear correlation?

<p>Caffeine intake has varying effects on alertness depending on the amount (B)</p> Signup and view all the answers

What does a negative lag value indicate in the context of parent-infant interactions?

<p>Parent's naming occurs 5-10 seconds before the infant's response (B)</p> Signup and view all the answers

Positive autocorrelation means that a behavior is decreasing over time.

<p>False (B)</p> Signup and view all the answers

What is autocorrelation?

<p>It tests whether a single variable at one timepoint is related to the same variable at another timepoint.</p> Signup and view all the answers

A positive correlation in depressive symptoms means that symptoms are _______ over time at specific intervals.

<p>increasing</p> Signup and view all the answers

Match the following terms with their definitions:

<p>Lag Cross-Correlations = Tests of association between a variable at an earlier timepoint and a later timepoint Autocorrelations = Tests if a single variable is associated with itself across time points Negative Lag = Parent's action occurs before the infant's response Positive Autocorrelation = Behavior increases over time</p> Signup and view all the answers

In infant development, what does the 'Lag' refer to?

<p>The time difference between the parent's action and infant's response (D)</p> Signup and view all the answers

Circadian rhythms are associated with repeating patterns that occur over a 12-hour cycle.

<p>False (B)</p> Signup and view all the answers

What association is being tested when measuring lag cross-correlations?

<p>The association between a variable at an earlier timepoint and another variable at a later timepoint.</p> Signup and view all the answers

In the context of pediatric development, when a child's behavior precedes a parent's action, it implies that the child is exhibiting _______ behavior.

<p>initiating</p> Signup and view all the answers

Match the following examples with their respective correlation types:

<p>Parent soothing behavior = Autocorrelation Infant turning head after parent names an object = Lag Cross-Correlation Weekly depression symptoms in bipolar disorder = Negative Autocorrelation Circadian rhythms = Regular repeating patterns</p> Signup and view all the answers

Which of the following would likely indicate a negative autocorrelation over time?

<p>Parent soothing decreases as time progresses (D)</p> Signup and view all the answers

When observing positive autocorrelation, behaviors remain stable with no change over time.

<p>False (B)</p> Signup and view all the answers

How often do depressive symptoms in bipolar disorder tend to repeat?

<p>Every 5-6 weeks.</p> Signup and view all the answers

The method used to observe if a behavior at one time point correlates with the same behavior at a different time point is known as _______.

<p>autocorrelation</p> Signup and view all the answers

Flashcards

Cross-Sectional Correlation

Examines the relationship between two variables measured at the same point in time.

Lag Cross-Correlation

Assesses if a variable at an earlier time is linked to another variable at a later time.

Autocorrelation

Measures the relationship of a variable to itself over time.

Bathing Frequency and CVD Risk

A study suggested a link between bathing frequency and a lower risk of cardiovascular disease.

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Temporal Precedence

The idea that one event happens before another.

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Correlation Strength

A measure of how strongly two variables are related.

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Correlation Direction

Indicates the nature of the relationship (positive, negative, or zero).

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Correlation Significance

Indicates if the identified correlation is likely due to chance or a real relationship.

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Correlational Strategy

A research method used to examine the relationship between two or more variables. It focuses on observing and measuring how changes in one variable affect changes in another.

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Scatterplot

A visual representation of the relationship between two variables. Each point on the plot represents a pair of measurements.

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Regression Line

A line drawn through the points on a scatterplot that best represents the overall trend in the relationship between the variables.

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Correlation Coefficient (r)

A numerical value that describes both the strength and direction of a linear relationship between two variables. It ranges from -1.0 to +1.0.

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Positive Correlation

A relationship where as one variable increases, the other variable also tends to increase. The correlation coefficient is positive.

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Negative Correlation

A relationship where as one variable increases, the other variable tends to decrease. The correlation coefficient is negative.

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No Correlation

No consistent relationship between two variables. The correlation coefficient is close to zero.

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Linear Correlation

A relationship where the changes between the two variables are consistent and can be represented by a straight line.

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Nonlinear Correlation

A relationship where the changes between the two variables are not consistent and cannot be represented by a straight line.

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Spearman's Rank-order Correlation (rs)

A statistical method used to determine the strength and direction of the monotonic relationship between two ordinal variables.

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Lag

The time difference between when a parent names an object and when an infant looks at it.

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Negative Lag

The parent's action occurs before the infant's response.

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What does a negative lag tell us?

The infant's response is slow or delayed.

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Positive Autocorrelation

The relationship of a variable to itself is consistent over time.

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Negative Autocorrelation

The relationship of a variable to itself is opposite over time.

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Circadian Rhythm

A natural biological cycle that repeats roughly every 24 hours.

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Autocorrelation and Circadian Rhythm

Autocorrelation can be used to analyze cyclical patterns like circadian rhythms.

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Depressive Symptoms and Autocorrelation

Autocorrelation can highlight patterns in depressive symptoms over time.

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Positive Autocorrelation and Depression

Depressive symptoms tend to be similar at similar time points within a cycle.

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Negative Autocorrelation and Depression

Depressive symptoms tend to be opposite at different time points within a cycle.

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Correlation and Outcomes

Correlations can provide valuable insights into the relationship between variables.

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Temporal Precedence in Correlations

The cause (independent variable) must happen before the effect (dependent variable).

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Correlation Does Not Equal Causation

Just because two variables are related doesn't mean one causes the other.

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Study Notes

Correlational Research Strategy

  • Correlational research aims to demonstrate a relationship between two variables, but does not establish cause-and-effect.
  • Experimental research, in contrast, demonstrates a cause-and-effect relationship between two variables.
  • Correlational strategy is used to study the relationship between two or more variables.
  • Correlation describes the direction and degree of relationship between variables.
  • Data collection is strictly correlational, meaning no variables are manipulated; variables are measured.
  • Observation, surveys, and physiological measurements are common methods of data collection.
  • Correlational research has high external validity, meaning it can be generalized to real-world settings, but it does not allow for conclusions about causality.
  • A study examining the relationship between cheese consumption and deaths from bedsheet tangling has a high correlation but cannot imply causation.
  • Examples of correlational studies include the relationship between chocolate price and quality (marketing), caffeine intake and alertness (basic research), and movie topics and music preferences (art design).
  • Scatter plots are used to visualize the relationship between variables in correlational studies. Each point on a scatterplot represents one measurement.
  • Each item or person is represented by only one data point on a scatter plot. Each point is assumed to be independent of others in the data set. In other words, no two points can come from the same individual.

Correlation Coefficient

  • A correlation coefficient (r) quantifies the strength and direction of a linear relationship between two variables. The values range from -1.0 to +1.0. The sign denotes the direction of the correlation.
  • For ordinal data, Spearman's rank order correlation (rs) is used.
  • For ratio or interval data, Pearson correlation (r) is used.
  • A correlation coefficient of 1.0 or -1.0 indicates a perfect linear relationship.
  • Values near zero suggest a weak linear relationship.

Nonlinear Correlations

  • A linear correlation shows a consistent change in one variable as the other variable changes.
  • A nonlinear correlation shows inconsistent changes.

Spearman's Rank-Order Correlation

  • Spearman's correlation quantifies the strength and direction of a monotonic relationship between two ordinal variables.
  • Monotonic relationship means that the two variables move in the same direction (i.e., both increasing or decreasing).

When to Use Spearman's Rank-Order Correlation

  • Spearman's rank-order correlation is used when the data is ordinal and not interval or ratio scale.
  • Monotonic relationships must be identified for the data to be meaningful using Spearman's correlation coefficient.

Calculating a Spearman Correlation

  • Raw data scores are used to compute a Spearman rank correlation.
  • Data is ranked from lowest to highest.
  • The difference between the ranks is calculated for each score pair.

Calculating a Pearson Correlation

  • A correlation coefficient describes the relationship between two variables, quantifying the direction and strength of a linear relationship.
  • Direction, form, and consistency are the three characteristics a correlation assesses.
  • Interval or ratio scale data is common in behavioral research.

Direction of Correlation

  • Positive correlation: Higher values of one variable tend to be associated with higher values of the other variable; lower values of one variable tend to be associated with lower values of the other.
  • Negative correlation: Higher values of one variable tend to be associated with lower values of the other variable and vice versa.
  • No, or zero, correlation: There is no observable, predictable relationship between variables.

Form of Correlation

  • Linear relationship: Data points tend to cluster around a straight line.
  • Positive linear relationship: One variable increases consistently with a predictable increase in the other variable at a similar rate.
  • Nonlinear relationship: Data points do not cluster around a straight line; these often follow a curve.
  • The Pearson correlation is used to assess linear correlations, while Spearman's rank correlation assesses monotonic relationships.

Strength of Correlation

  • The strength of a correlation is determined by the absolute value of the correlation coefficient, which ranges from -1.0 to +1.0.
  • A value close to 1 or -1 indicates a strong relationship. A value close to 0 indicates a weak relationship.
  • The magnitude of a correlation coefficient is ordinal such that a value of .8 is not twice as strong as .4.

Correlation: Outliers

  • Outliers are data points that deviate significantly from the general trend of the data set, which can strongly influence the correlation.
  • Outliers are common in measures of variance, meaning that they can be 2-3 standard deviations from the mean value.

Correlations in Spearman & Pearson

  • Spearman correlation is less sensitive to outliers than Pearson correlation.
  • Re-assigning ranks addresses outlier issues in Spearman, which is advantageous.

Correlation: Significance and Interpretation of Value

  • Statistical significance tests determine if a correlation is unlikely due to chance.
  • A low p value suggests it is a real relationship that likely exists in the population.
  • Small sample sizes increase the chance of observing high correlations even when there is no relationship in the population, and vice versa.
  • A p-value less than 0.5 is often used as a criterion to denote a statistically significant correlation.

Correlation and Outcomes

  • Cross-sectional correlations test if two variables measured simultaneously are related to one another.
  • Lagged cross-correlations determine if one variable precedes another variable in time.
  • Autocorrelations investigate whether the same variable measured at different points in time are related.
  • Correlational methods do not establish causality, but they can provide valuable insight into relationships between variables.

Advantages of Correlational Methods

  • Often quick and efficient.
  • Sometimes the only method available due to practical or ethical constraints, such as the inability to manipulate a variable like personality traits or due to ethical considerations.
  • Reflect natural events.
  • Higher degree of external validity.

Limitations of Correlational Methods

  • Does not indicate causation.
  • Variable values are sensitive to outside variables, which may influence the data set.
  • Directionality problem: Variables cannot reliably be identified as a cause and effect relationship.
  • Third-variable problem: A third unknown variable is likely influencing the data relationship between variables.

Timepoint-Based Correlations

  • Cross-sectional correlations: relationships between variables at a single time point.
  • Lagged correlations: Relationships between an earlier variable and a later variable.
  • Autocorrelations: Relationships between a variable measured at different points in time.

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Chapter 12: The Correlational Research Strategy PDF

Description

Explore the fundamentals of correlational research strategies. This quiz covers the key concepts, methods, and implications of correlational versus experimental research. Test your understanding of how relationships between variables are studied and the importance of not implying causation.

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