Research Methods

RESEARCH METHODS

Overview of Research Methods

  • Research methods are systematic approaches to collect data, analyze findings, and derive conclusions to explore psychological and behavioral phenomena.

Group Level Research Methods

  • Most Common Type of Research:

    • Group-level research is the frequently utilized method in scientific studies. It allows for drawing conclusions and evaluating different treatments across various conditions.

Controlled Group Designs
  • Definition:

    • Experiments in which groups of participants are exposed to different conditions, including at least one experimental group and one control group.

  • Key Components:

    • Independent Variable (IV): Variable that is manipulated or controlled by the experimenter.

    • Dependent Variable (DV): Variable that is measured to determine the effect of the IV.

  • Methodologies:

    • Random Assignment: Ensures that participants have an equal chance of being assigned to any group, promoting internal validity. ( helps de likelihood internal validty of the treatments )

    • Internal Validity: The extent to which a study accurately measures the relationship between the independent and dependent variables.

    • External Validity: The generalizability of the research findings to real-world settings. ( expand to more ppl , how much )

    • efficacy; you have to show how your tretamnets works

    • effectiveness ; si funcionq , se convierte para mucha poblacion

    • Comparison:

    • Distinction between internal validity and external validity is essential for discerning between efficacy (effectiveness in controlled environments) and effectiveness (real-world application).

  • Clinical vs. Statistical Significance:

    • Clinical significance refers to the practical importance of a treatment effect, while statistical significance denotes whether the results obtained are likely due to chance.( meaningful for ghe ppl who participated in the study , the person se tiene que sentir mejor ensu vida , un cambio )

    • Statistical: happens by chance less than 5% of the time

Correlational Method
  • Definition:

    • The Relationship between variables is measured using a correlation coefficient.

  • Correlation Coefficient:

    • Indicates both direction and strength of the relationship between variables.

    • Ranges from -1.0 to 1.0, with positive and negative correlations:

    • Positive Correlation: Indicates that as one variable increases, the other also increases.

    • Negative Correlation: Indicates that as one variable increases, the other decreases.

    • 0.1-0.3 weak

    • 0.4-0.5 moderate

    • 0.6-0.9 strong

  • Key Point:

    • "Correlation does not imply causation," emphasizing that a correlation between two variables does not mean one causes the other.

Example of Positive Correlation

  • Scenario:

    • Day-by-day tracking of cigarettes smoked per day vs. scores on an anxiety scale.

  • **Data Table: **

    • Day | # of Cigarettes Smoked/Day | Score on Anxiety Scale

    • --- | --- | ---

    • 1 | 5 | 2

    • 2 | 15 | 10

    • 3 | 4 | 3

    • 4 | 13 | 11

    • 5 | 10 | 9

    • 6 | 17 | 13

    • 7 | 7 | 5

    • 8 | 6 | 3

    • 9 | 21 | 15

  • Visualization:

    • Graphical representation showing the correlation between the number of cigarettes smoked per day and anxiety scores.

  • Statistical Analysis:

    • Pearson's r coefficient: 0.97

    • Probability of occurrence by chance ( p < .05): Probability indicates that this high correlation is statistically significant, with a chance occurrence rate of less than 5%.

Further Example of Positive Correlation
  • Correlation between Final Grade and Attendance in Abnormal Psychology:

    • Data indicates a high positive correlation where:

    • Pearson's r coefficient: 0.66

    • Probability of this correlation occurring by chance: p < .05 (actual p value = .001)

Research Design Types

  • Cross-sectional Design:

    • Participants are assessed once for the specific variable under investigation, providing a snapshot of the data at one point in time.

  • Longitudinal Design:

    • Participants are assessed at least twice over a certain time interval, allowing researchers to observe changes over time.

  • Cohorts:

    • A cohort is defined as a group of people who share a common characteristic and move forward in time as a unit, beneficial for longitudinal research approaches.