Skip Navigation
Facts From NLTS2: Orientation and Mobility Skills of Secondary School Students With Visual Impairments
NCSER 2008-3007
November 2007

Demographics and School Settings

The demographic characteristics of students with visual impairments do not differ significantly from those of students in the general population (figure 1). Approximately half are male, 61 percent are white, 20 percent are African American, 13 percent are Hispanic, and 15 percent live in households with incomes below the poverty level.

School personnel reported that 60 percent of students in the category of visual impairment have no coexisting disabilities (figure 2); however, approximately 21 percent have one other disability, and 19 percent have two or more additional disabilities. The most common coexisting disabilities for students categorized as visually impaired are mental retardation and learning disabilities (41 percent and 37 percent, respectively, of students with visual impairments and coexisting disabilities). Parents reported that 28 percent of students in the category of visual impairment are blind and 72 percent are partially sighted (figure 3).

The majority of students categorized as having a visual impairment (81 percent) attend regular schools. These students are significantly less likely to have coexisting disabilities than students attending special schools serving only students with disabilities (31 percent vs. 74 percent, p < .001, figure 4)4. Further, at special schools, the percentage of blind students is larger than at regular schools (54 percent vs. 21 percent, p < .001).

4 In this report, tests of equality of proportions were performed to determine differences between groups and are highlighted only if the differences are statistically significant with at least 95 percent confidence (denoted as p < .05). Statistical tests examining differences between independent subgroups or between responses to different items given by the same group that involve categorical variables with more than two possible response categories were conducted by treating each of the possible response categories as separate dichotomous items. The test statistic used to compare Bernoullian-distributed responses (i.e., responses that can be allocated into one of two categories and coded as 0 or 1) for two independent subgroups is analogous to a chi-square test for equality of distribution (Conover 1971) and approximately follows a chi-square distribution with one degree of freedom. However, because the test statistic itself is more similar in form to the square of a two sample t statistic with unequal variances (Satterthwaite 1946), and because a chisquare distribution with one degree of freedom is the same as an F distribution with one degree of freedom in the numerator and infinite degrees of freedom in the denominator (Johnson and Kotz 1970), this statistic can be considered the same as an F value; it also can be considered "X2". To calculate whether the difference between percentages are statistically significant, the squared difference between the two percentages of interest is divided by the sum of the two squared standard errors. If the resulting number is larger than 3.84, the difference is statistically significant at the .05 level—i.e., it would occur by chance fewer than 5 times in 100 (the approximate number of comparisons contained within this report). Presented as a formula, a difference in percentages is statistically significant at the .05 level if:
(P1 P2)2/SE12 + SE22> 1.962
where P1 and SE1 are the first percentage and its standard error and P2 and SE2 are the second percentage and the standard error. If the result of this calculation is 6.63 to 10.79, the significance level is .01, and products of 10.8 or greater are significant at the .001 level. No special adjustments were made to account for multiple comparisons. Given the number of comparisons made in this report, readers are cautioned to consider the possibility of false positives in interpreting the data.