Related Experiment Video
Updated: Jun 30, 2025
08:12
A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
Published on: March 1, 2022
2.5K
Evaluating Paired Categorical Data when the Pairing is Lost
R N Montgomery1, A S Watts2, N C Burns3
1The University of Kansas Medical Center, Department of Biostatistics, Kansas City, KS.
Journal of Applied Statistics
|March 20, 2024
Summary
This study assessed the Self-Revelatory Performance intervention's impact on Alzheimer's disease perceptions. A modified bootstrap approach found evidence the intervention significantly influenced participants' views.
Area of Science:
- Psychology
- Neuroscience
- Public Health
Background:
- Assessing interventions for Alzheimer's disease perceptions is crucial.
- Data integrity issues, such as lost pairing in experimental designs, can complicate analysis.
- The Self-Revelatory Performance intervention aimed to alter views on Alzheimer's disease.
Purpose of the Study:
- To evaluate the effectiveness of the Self-Revelatory Performance intervention.
- To determine if the intervention impacted participants' perceptions of Alzheimer's disease.
- To address challenges posed by lost data pairing in the study design.
Main Methods:
- Utilized a modified bootstrap approach to analyze pre- and post-intervention data.
- Employed an Affect grid to measure participant responses before and after the intervention.
- Calculated the distance between the Centers of Mass of the Affect Grids as the test statistic.
Main Results:
- The modified bootstrap approach allowed for the creation of a null hypothesized distribution.
- The null hypothesis was rejected, indicating a statistically significant effect.
- Evidence suggests the intervention altered participants' perceptions of Alzheimer's disease.
Conclusions:
- The Self-Revelatory Performance intervention demonstrated a significant influence on perceptions of Alzheimer's disease.
- The modified bootstrap method proved effective in handling lost data pairing.
- This study provides valuable insights into intervention strategies for Alzheimer's disease perception.
More Related Videos
07:34Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Published on: June 3, 2013
17.3K
10:00Methods of Pairing and Pair Maintenance of New Zealand White Rabbits Oryctolagus Cuniculus Via Behavioral Ethogram, Monitoring, and Interventions
Published on: March 16, 2018
14.0K
Related Concept Videos
01:09Wilcoxon Signed-Ranks Test for Matched Pairs
123
The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
123
01:17Sign Test for Matched Pairs
131
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
To conduct the sign test, we first calculate the differences in...
131
01:29Contingency Table
2.5K
A contingency table provides a way of portraying data that can facilitate calculating probabilities. It is a method of displaying a frequency distribution as a table with rows and columns to show how two variables may be dependent (contingent) upon each other; The table helps determine conditional probabilities quite quickly and can help systematically organize, analyze and quantify data. The table displays sample values concerning two variables that may be dependent or contingent on one...
2.5K
01:15One-Way ANOVA: Unequal Sample Sizes
5.8K
One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
5.8K
01:23McNemar's Test
234
McNemar's Test is a nonparametric statistical test used to determine if there is a significant difference in proportions between two related groups when the outcome is binary (e.g., yes/no, success/failure). It is beneficial when we have paired data, such as pre-test/post-test designs, where the same subjects are measured under two different conditions. The test is named after the statistician Quinn McNemar, who introduced it in 1947. It is commonly used in situations where subjects are...
234
01:20Comparing the Survival Analysis of Two or More Groups
183
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
183