Abstract
This study investigated associations between working memory(measured by complex memory tasks) and both reading and mathematicsabilities, as well as the possible mediating factors of fluidintelligence, verbal abilities, short-term memory (STM), andphonological awareness, in a sample of 6- to 11-year-olds withreading disabilities. As a whole, the sample was characterized bydeficits in complex memory and visuospatial STM and by low IQscores; language, phonological STM, and phonological awarenessabilities fell in the low average range. Severity of readingdifficulties within the sample was significantly associated withcomplex memory, language, and phonological awareness abilities,whereas poor mathematics abilities were linked with complex memory,phonological STM, and phonological awareness scores. These findingssuggest that working memory skills indexed by complex memory tasksrepresent an important constraint on the acquisition of skill andknowledge in reading and mathematics. Possible mechanisms for thecontribution of working memory to learning, and the implicationsfor educational practice, are considered.
Citation:Gathercole, S. E., Alloway, T. P., Willis, C.,& Adams, A. M. (2006). Working memory in children with readingdisabilities. Journal of Experimental Child Psychology, 93(3),265-281.
Dataset:
- Dependent variable (Y): Reading - reading skills ofthe 6 to 11 year olds
- Independent variables (X):
- Verbal - a measure of verbal ability(spelling, phonetics, etc.)
- Math - a measure of math ability
- Work_mem - working memory score
Data screening:
Accuracy
Assume the data is accurate with no missing values. You willwant to screen the dataset using all the predictor variables topredict the outcome in a simultaneous multiple regression (all thevariables at once). This analysis will let you screen for outliersand assumptions across all subsequent analyses/steps.
Outliers
a. Leverage:
i. What is your leverage cut offscore?
ii. How many leverage outliers did youhave?
b. Cook's:
i. What is your Cook's cut offscore?
ii. How many Cook's outliers did youhave?
c. Mahalanobis:
i. What is your Mahalanobisdf?
ii. What is your Mahalanobis cut offscore?
iii. How manyoutliers did you have for Mahalanobis?
d. Overall:
i. How many total outliers didyou have across all variables?
ii. Delete them!
Hierarchical Regression:
a. In step 1, control for verbal ability of the participantpredicting reading scores.
b. In step 2, test if working memory is related toreading scores.
c. In step 3, test if math score is related to readingscores.
d. Include the summaries of each step, along with theANOVA of the change between each step.
Moderation:
a. Examine the interaction between verbal and math scorespredicting reading scores.
b. Include the simple slopes for low, average, and high math levels(split on math) for verbal predicting reading.
c. Include a graph of the interaction.
