e structure containing many errors that inhibit clarity
or fluency (Rust, 1996). Measures of ideas and development (M = 1.5, SD
= .73), vocabulary (M = 1.47, SD = .73), and organization and coherence
(M = 1.57, SD = .79) were also in the low range. A Freidman's
Analysis indicated that the scores differed statistically significantly
across the subtests ([chi square] = 25.86, df = 5, p < .0005).
Measures of grammar and capitalization did not differ from each other (z
= .564, ns). There were significant differences between grammar compared
with organization and coherence (z = -2.138, p = .03), ideas and
development (z = -2.558, p = .01), vocabulary (z = -3.500, p <
.0005), and sentence structure (z = -3.638, p < .0005). Scores for
capitalization were significantly better than vocabulary (z = -2.683, p
= .007) and sentence structure (z = -3.153, p = .002), but did not
differ statistically from the measures of ideas and development (z =
-1.908, ns) or organization and coherence (z = -1.414, ns). The measure
of organization and coherence was significantly better than vocabulary
(z = -2.121, p = .03) but did not differ from ideas and development (z =
-1.00, ns) or sentence structure (z = -1.748, ns). Ideas and
development, vocabulary, and sentence structure did not differ
significantly from each other (z = -.577, ns; z = -.832, ns; z = -.302
We computed a factor analysis to investigate further the pattern of
subtest relationships. The factor analysis met all the necessary
statistical assumptions; we considered only those factors with
eigenvalues greater than 1.0. The analysis generated a single factor
solution accounting for 83% of the variance. There were large and
significant loadings (.87) for all of the WOLD (Wechsler, 1996)
Writing Trajectories Over Time. Data for the total analytic score
of the WOLD (Wechsler, 1996) were available for 51 participants at four
time points (ages 11, 12, 14, and 16). Four participants had refused to
write at 11, and data were missing for 1 student at age 12 and 2
participants at age 14. There was no significant difference between
writing scores at age 16 for participants with missing data (M = -2.66)
and those with data for all four time points (M = -2.14, t = 1.159, df =
56, ns). As Figure 1 shows, there was a significant decrease in relative
performance as measured by z scores, F(3, 150) = 23.888, p < .0005,
[eta][p.sup.2] = .32. Post hoc comparisons of z scores adjusting for
multiple comparisons indicated that the participants' writing
performance at age 11 was significantly better than their performance at
age 12 (p = .002), 14 (p = .002), and 16 (p < .0005). Performance at
age 12 and age 14 did not differ whereas there was a significant decline
in performance again at age 16 (p < .0005 for both ages 12 and 14).
[FIGURE 1 OMITTED]
Although the mean drop between ages 11 and 16 was one SD (M = 1.0),
patterns of change varied across participants. A change score was
computed where the z score at age 11 was subtracted from the z score at
age 16, thereby providing a pattern of change across 5 years, where
positive scores would indicate a relative increase in writing
performance. Table 3 presents the relationships between literacy,
language, and nonverbal abilities and change scores. Using a Bonferroni
correction of .004 for multiple correlations there were significant
relationships between WOLD change score handwriting fluency (r = .54, p
< .0005; Wechsler, 1996) and spelling (r = .38, p = .006). There were
no significant relationships with nonverbal ability, vocabulary, reading
decoding, and reading comprehension. We examined this pattern of
relationships using multiple regression. In all cases residuals were
normally distributed. The extent of the relationship between gain score
and handwriting fluency was confirmed with a multiple regression
controlling for nonverbal ability which revealed a significant model,
F(2, 49) = 9.689, p < .0005) accounting for 29% of the variance.
Fluency was the only significant predictor in the model ([beta] = .479);
the less fluent students were in producing the