37 25 and 14 infants respectively were excluded from analysis due to motion or

37 25 and 14 infants respectively were excluded from

This preview shows page 5 - 7 out of 16 pages.

37%, 25%, and 14% infants, respectively, were excluded from analysis due to motion- or inattention-related eye-tracker calibration failure. There was no differential dropout by risk status at 6, 9, or 12 months ( X 2 [1] = .47, p = .495; X 2 [1] = 1.31, p = .252; X 2 [1] = .04, p = . 839, respectively). After these initial exclusions, eye-tracking data from 94 (59 HR, 20 females, and 35 LR, 15 females) 6-month-olds, 107 (68 HR, 22 females, and 39 LR, 14 females) 9-month-olds, and 132 (81 HR, 23 females, and 51 LR, 22 females) 12-month-olds were analyzed. Chawarska et al. Page 5 J Am Acad Child Adolesc Psychiatry . Author manuscript; available in PMC 2018 February 15. Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Image of page 5
Statistical Analysis Primary hypotheses were tested with age (3) x risk status (2) x sex (2) linear mixed models. Severity of ASD symptoms—ADOS Social Affect (SA) and ADOS Restricted, Repetitive Behaviors (RRB) scores—were included into the models as continuous measures of autism symptom severity at 24 months. Planned contrasts were conducted between HR males and females, LR males and females, HR and LR males, and HR and LR females. The magnitude of effects was quantified with Cohen’s d . Given detected risk group and sex differences in Verbal (V) and nonverbal (NV) developmental quotients (DQ), these measures were included in the models as covariates. All planned contrasts are reported with a Tukey- Kramer correction for multiple comparisons. In alternative analyses, we applied arcsine followed by Box-Cox transforms to data and verified linearity, homogeneity, and residual normality via diagnostic plots and Lilliefors test. Patterns of significance were almost identical. This was expected due to the robustness of linear mixed models. 43-45 For this reason, and to maintain comparability to prior work 17,23-25 and to aid reproducibility, no transformations on data were used in analyses presented here. Associations between eye- tracking measures and phenotypic characteristics were evaluated using Pearson’s r correlation coefficient analysis. Data analyses were implemented in SAS 9.3. RESULTS Preliminary Analyses Analysis of developmental skills and severity of autism symptoms revealed an expected pattern of results. An age x risk status x gender analysis of verbal developmental quotient (VDQ) indicated significant effects of age ( F [2, 184] = 131.35, p <.001) and risk status ( F [1, 168] = 7.41, p = .007 [ d = -.30]), and an age x gender interaction ( F [2, 184] = 4.64, p = .01). VDQ scores increased significantly between 6 and 12 ( p < .001) and 12 and 24 ( p < .001) months. High-risk infants performed more poorly than low-risk infants. Females outperformed males at 12 ( p = .026, d = .56) and 24 months ( p = .011, d = .45 ), but not at 6 months ( p = .257). No other simple or interaction effects were significant. For nonverbal DQ (NVDQ), there were significant effects of age ( F [2, 184] = 61.25, p < .001), gender ( F [1, 168] = 8.11, p = .005 [ d = .38]), and risk status ( F [1, 186] = .6.29, p = .013 [ d = -.40]). The scores increased from 6 to 12 months ( p < .001) and from 12 to 24 months ( p = .002). High- risk infants performed more poorly than low-risk infants, and females outperformed males.
Image of page 6
Image of page 7

You've reached the end of your free preview.

Want to read all 16 pages?

  • Fall '15
  • WYLLIE
  • The Land, Katarzyna Chawarska

What students are saying

  • Left Quote Icon

    As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

    Student Picture

    Kiran Temple University Fox School of Business ‘17, Course Hero Intern

  • Left Quote Icon

    I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

    Student Picture

    Dana University of Pennsylvania ‘17, Course Hero Intern

  • Left Quote Icon

    The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

    Student Picture

    Jill Tulane University ‘16, Course Hero Intern

Stuck? We have tutors online 24/7 who can help you get unstuck.
A+ icon
Ask Expert Tutors You can ask 0 bonus questions You can ask 40 questions (40 expire soon) You can ask 40 questions (will expire )
Answers in as fast as 15 minutes