Penetrating the Classroom Social Network for Children With Language Impairment Via Peer Mediated Intervention
Phase: NA
Conditions: Peer Influence
Sponsor: Ohio State University

Research Protocol 
Network-Based Classroom Intervention for Language Impairment 
 
PI: Laura Justice 
 
I.Objectives 
The goal of this study is to apply a social-network approach to investigate the effects of a 
peer-mediated intervention to improve socialization processes in preschool inclusive classrooms 
for children with language impairment, as a mechanism for improving interactions with peers, 
exposure to peer talk, and children’s social, behavioral, and linguistic skills. 
II.Background and Rationale 
Language impairment (LI) is a high-incidence developmental disability that significantly 
elevates a child’s susceptibility for peer maltreatment, including exclusion from peer social 
networks and victimization by peers. Studies find, for instance, that nearly 40% of preschoolers 
with LI are excluded from their classroom social network (Justice, Chen, Jiang, Tambyraja, & 
Logan, 2019)  and a similar percentage of primary-grade pupils with LI are regularly victimized 
by their peers (Conti-Ramsden & Botting, 2004). These circumstances reflect in part the 
relatively poor social competence and pragmatic-language skills of children with LI 
(Longobardi, Spataro, Frigerio, & Rescorla, 2016), but also the socialization processes that 
characterize classroom settings. Specifically, as early as the preschool years, children 
demonstrate strong homophilic behaviors in establishing peer relationships in their classrooms 
(Chen, Lin, Justice, & Sawyer, 2019), preferring to play with others of the same gender, age, 
skill levels, and disability status. In preschool settings, children with LI tend to interact most 
frequently with other children with LI, even in inclusive settings serving children with 
disabilities and typically developing peers (Justice, Chen, et al., 2019).  
The social difficulties experienced by children with LI, particularly social exclusion, can lead 
to numerous adversities in the short and longer term; this includes school avoidance and 
disliking, dis-engagement in classroom learning activities, academic under-achievement, and 
escalating externalizing behaviors (Buhs & Ladd, 2001; Bulotsky-Shearer et al., 2012; Fantuzzo, 
Sekino, & Cohen, 2004; Nakamoto & Schwartz, 2010).  Peer maltreatment via social exclusion 
also inhibits the opportunity for children with LI to interact with peers with more sophisticated 
language skills, representing a key mechanism for improving the language skills of children with 
LI in inclusive classroom settings via well-documented ‘peer effects’ (Justice, Logan, Lin, & 
Kaderavek, 2014a). Peer effects is the phenomenon in which children’s language growth is 
positively linked to their classmates’ level of linguistic ability (Justice et al., 2014a). Peer effects 
have been measured by comparing the performance of individual students to the aggregated 
score of the group to examine effects on literacy, self-regulation, and development (Chen et al., 
2019). These methods may capture a global overview of interactions, but are limited in capturing 
the more in-depth experiences of individual children and their teachers. The mechanism by 
which those peer effects work is not typically measured. 

In the proposed study, we apply a social-network approach to investigate the effects of a 
peer-mediated intervention to improve socialization processes in preschool inclusive classrooms 
for children with LI, as a mechanism for improving interactions with peers, exposure to peer talk, 
and children’s social, behavioral, and linguistic skills. We build upon a large body of work 
showing the positive effects of peer-mediated interventions, especially for children with autism 
spectrum disorder, but innovate further by (1) studying this approach for children with LI, (2) 
applying advanced technologies from computer engineering to rigorously explore social 
processes for children with LI targeted by the intervention, and (3) using social network indices 
in addition to child-level outcomes to assess intervention effects.   
The specific goals for this study are: 
1. To determine the extent to which peer-mediated pivotal response training yields direct 
effects on peer social interactions for children with LI in the classrooms social network. 
2. To determine the extent to which peer-mediated pivotal response training yields indirect 
(mediated) effects on the social, behavioral, and linguistic skills of children with LI 
3. To determine the extent to which peer-mediated pivotal response training targeting focal 
children may broadly effect the social network dynamics at the classroom level. 
 
III. 
Procedures 
a. Research Design 
In order to validate the technology, the research team will conduct a small pilot in the 
summer of 2021 in two central Ohio classrooms.  The goal of this small pilot is to ensure the 
accuracy, validity, and feasibility of technology and observation instruments that will be used in 
the large study overviewed below.  This pilot study involves 2 inclusive preschool classrooms 
and an estimated 40 3- to 5- year-old children from these classroom, comprising approximately 
25 children with disabilities and 15 typically developing peers.  Sample estimates are based on 
the same calculations used in the larger study that are overviewed in the paragraph below.  The 
same classroom eligibility criteria will be used for the pilot as the larger study (i.e., an eligible 
classroom must serve > 3 children with educational determination of LI per a certified speech-
language pathologist).  The study team will use the same method to establish focal children and 
peers as the larger study overviewed below (Focal children (n = 1 per classroom): First, we 
identify all children’s positions within the classroom social network using a teacher matrix 
(TRPI) conducted in summer 2021; from this network we calculate a child-level social network 
index (i.e., individual degree centrality; lower scores are characteristic of social exclusion 
(Justice, Chen, et al., 2019)). Second, teachers simultaneously complete the Developmental 
Pragmatic Profile (DPP) (Wiig, Secord, & Semel, 2004) for each child in the classroom. This is a 
26-item psychometrically sound checklist assessing children’s pragmatic skills (e.g., 
conversational abilities, giving information), and DPP scores have strong classification accuracy 
in differentiating children with LI from non-affected classmates (Justice, Ahn, & Logan, 2019). 
Third, teachers also use a checklist to identify children with LI in each classroom per four 
criteria: the child (1) is on the caseload of a speech-language pathologist, (2) has no known 
additional diagnoses causal of LI, such as ASD, (3) primarily communicates in English, and (4) 

is greater or equal than 42 months of age. Finally, among the children with LI, we select the 
target child based on the lowest centrality scored weighted by DPP score, so that focal children 
represent the most socially isolated children with the poorest social-pragmatic communication 
skills.   
The two classrooms/teachers participating in the pilot will complete a 6 week suite of 
activities to include: trainings, three storybook readings and corresponding peer mediated 
strategy facilitations during weeks (e,g,. Monday, Wednesday, Friday), observation of 
facilitation sessions by research staff 
The main study involves 90 inclusive preschool classrooms/90 teachers and an estimated 
900 3- to 5-year-old children from these classrooms, comprising approximately 770 children 
(approximately 423 of which have diagnosed disabilities) and 770 parents (N=1630). Sample 
estimates are based on Ohio’s inclusive model of preschool special education and our prior work 
in these settings, in which 55% of students have disabilities (Justice, Logan, Lin, & Kaderavek, 
2014b). For the proposed study, an eligible classroom must serve > 3 children with educational 
determination of LI per a certified speech-language pathologist.  
The study uses a wait-list experimental design to estimate treatment impacts, with 30 
ohio classrooms assigned to the treatment condition and 20 to the control condition. All 
remaining 40 classrooms will be recruited by our partners at external sites and serve control 
condition classrooms.  Within each classroom, the focal participants are 30 children with LI, one 
selected per classroom using a priori exclusionary and inclusionary criteria. The wait-list design 
allows eligible children with LI in control classrooms to receive treatment in the spring semester; 
this also allows for ongoing evaluation of changes in socialization processes in treatment 
classrooms through spring. Study methods with OSU classrooms use a sequential cohort design, 
with 15 classrooms participating in each of two consecutive years to disperse study activities 
over a 24-month period. Classrooms will be recruited via our extensive network of affiliated 
preschool programs across the state of Ohio, with eligible classrooms utilizing a 50/50 inclusive 
service delivery model (50% of children with disabilities). In the fall of each year, once all 15 
classrooms are recruited, simple random assignment will be used to allocate 10 classrooms to the 
treatment group and 5 to the control group, with the latter implementing intervention in spring 
per the wait-list design.   In addition, our colleagues at the University of Kansas, are employing 
similar observation methods.  We will thus incorporate 20 classrooms (University of Kansas) to 
serve as control condition classrooms, allowing for a more robust sample of natural conditions in 
preschool classrooms across contexts. 
 
b. Sample 
This study examines the socialization experiences of preschool children with LI inclusive 
classrooms and the entire classroom social network. Thus, we seek to consent all children in each 
classroom as participants in this study. For children who are not focal children or peers assisting 
with the intervention, we will seek caregiver consent to observe their children in the classroom 
and for caregivers to complete a simple questionnaire about their children. We typically are able 
to actively or passively consent 90% of children in a classroom.   

Focal children (n = 30). We describe inclusionary and exclusionary criteria for the 30 
focal children with LI. First, we identify all children’s positions (n = 495) within the classroom 
social network using a teacher matrix conducted in fall of the academic year; from this network 
we calculate a child-level social network index (i.e., individual degree centrality; lower scores 
are characteristic of social exclusion (Justice, Chen, et al., 2019)). Second, teachers 
simultaneously complete the Developmental Pragmatic Profile (DPP) (Wiig, Secord, & Semel, 
2004) for each child in the classroom. This is a 26-item psychometrically sound checklist 
assessing children’s pragmatic skills (e.g., conversational abilities, giving information), and DPP 
scores have strong classification accuracy in differentiating children with LI from non-affected 
classmates (Justice, Ahn, & Logan, 2019). Third, teachers also use a checklist to identify 
children with LI in each classroom per four criteria: the child (1) is on the caseload of a speech-
language pathologist, (2) has no known additional diagnoses causal of LI, such as ASD, (3) 
primarily communicates in English, and (4) is greater or equal than 42 months of age. Finally, 
among the children with LI, we select the target child based on the lowest centrality scored 
weighted by DPP score, so that focal children represent the most socially isolated children with 
the poorest social-pragmatic communication skills.   
c. Detailed Study Procedures  
Pilot: Children and teachers participate for a 6 week period, and primary procedures are 
described here. 
Main Study: Children and teachers participate for a 9-month period, and primary procedures are 
described here.  
 
Intervention Implementation   
 
Pilot: Focal children in the two classrooms participating in the pilot will receive peer-mediated 
PRT per procedures detailed by Brock et al.  (Brock, Dueker, & Barczak, 2018). PRT procedures 
are facilitated by a classroom facilitator—a classroom teacher or teaching assistant—who will 
receive ongoing training and support from research staff. Focal children receive peer-mediated 
pivotal response treatment. With carefully identified classroom peers, facilitators hold four 15-
minute training sessions with the peer group, each developing 1 of 4 strategies to use to engage 
with the target child. The facilitator explicitly identifies the focal child (‘buddy’) and asks the 
children to use four strategies to play with the child during center time: a) offer your buddy some 
play options; b) show and talk about how to play with your buddy; c) compliment your buddy; 
and d) show your buddy how to take turns. After the trainings are complete, the facilitator 
provides ongoing support to peers during center time to implement the strategies by regularly 
encouraging them and supporting them to use the strategies, praising them when they use the 
strategies well, and reviewing their interactions with the focal child at the end of center time. 
Facilitators provide this support during center time at least 3 times weekly for athe duration of 
the 6 week pilot. 

 
Main Study: Focal children in OSU-based treatment condition classrooms will receive peer-
mediated PRT per procedures detailed by Brock et al (Brock, Dueker, & Barczak, 2018). PRT 
procedures are facilitated by a classroom facilitator—a classroom teacher or teaching assistant—
who will receive ongoing training and support from research staff. Focal children receive peer-
mediated pivotal response treatment. With carefully identified classroom peers, facilitators hold 
four 15-minute training sessions with the peer group, each developing 1 of 4 strategies to use to 
engage with the target child. The facilitator explicitly identifies the focal child (‘buddy’) and 
asks the children to use four strategies to play with the child during center time: a) offer your 
buddy some play options; b) show and talk about how to play with your buddy; c) compliment 
your buddy; and d) show your buddy how to take turns. After the trainings are complete, the 
facilitator provides ongoing support to peers during center time to implement the strategies by 
regularly encouraging them and supporting them to use the strategies, praising them when they 
use the strategies well, and reviewing their interactions with the focal child at the end of center 
time. Facilitators provide this support during center time at least 3 times weekly for a 12-week 
period. 
Data collection 
  
Main Study and Pilot: Classroom social networks will be observed using: (1) researcher 
observations and (2) location tracking.  
Caregivers and teacher surveys and questionnaires will be collected in the following ways 
1) recorded on forms that are directly scanned into centralized study databases or 2) via an online 
TeleForm template accessed through a website link or on a tablet, or 3) via a survey in Qualtrics. 
All caregiver and teacher-report measures will use web links that automatically feed into a 
centralized database. Derived scores for specific measures are programmed for automatic 
computation. We will adhere to the highest standards in data management practices (McCartney, 
Burchinal, & Bub, 2006) to ensure the integrity of our data, including double-entry for any hand-
entered data and regular data audits. 
d. Measures and Instrumentation 
Researcher observations. Researcher observations of peer social interactions are 
adapted from a validated observation protocol (Schaefer, Light, Fabes, Hanish, & Martin, 2010).  
Pilot Study: Using trained, reliable observers blind to study hypotheses and classroom 
study condition, a ῀40-min observation session will be conducted in each classroom once per 
week during weeks 2-6 of the pilot.  The observer will observe the classroom during center time 
and use the list of peer and focal children to structure four partial interval observation cycles; in 
each cycle, the observer observes each child for 15 s followed by 15 s recording and then moves 
to the next child.  At the end of one cycle, the observer takes a 5-min break. When observed, 
each child is recorded for any interaction partners (up to five) based on presence of a verbal or 
physical exchange or parallel play in the same activity during the 15-s observation. Reliability 
estimates will be assessed for 10% of cycles via double-coding. Based on researcher 

observations, a social network will be created for each classroom per observation window. It will 
be stored in a symmetric square matrix, where the rows and columns represent the classroom 
roster and each cell value refers to the frequency at which the pair of children play with each 
other.  
Main Study: Using trained, reliable observers blind to study hypotheses and classroom 
study condition, a ῀40-min observation session will be conducted in each classroom 8-16 times 
over the academic year. The observer will observe the classroom during center time and use a 
randomized list of children to structure four partial interval observation cycles; in each cycle, the 
observer observes each child for 15 s followed by 15 s recording and then moves to the next 
child. At the end of one cycle, the observer takes a 5-min break. When observed, each child is 
recorded for any interaction partners (up to five) based on presence of a verbal or physical 
exchange or parallel play in the same activity during the 15-s observation. Reliability estimates 
will be assessed for 10% of cycles via double-coding. Based on researcher observations, a social 
network will be created for each classroom per observation window. It will be stored in a 
symmetric square matrix, where the rows and columns represent the classroom roster and each 
cell value refers to the frequency at which the pair of children play with each other.  
Location tracking.  
Pilot: We augment researcher observations with automated continuous location tracking 
to capture children’s social contact with each other in the classroom. The tracking approach 
compensates researcher observation by continuously capturing peer social contact across 
classroom activities and context.  For the present purposes, we will use pilot observation to 
validate the system of indoor location tracking to be used in the main study. For the purposes of 
the pilot, we will validate a Bluetooth-based identification and proximity detection system only. 
The Bluetooth tags, also called beacons, will be worn by children and teachers 3 per week during 
weeks 2-6 of the pilot.  The goal is to ensure accuracy and feasibility during the main study.  
Main Study: We augment researcher observations with automated continuous location 
tracking to capture children’s social contact with each other in the classroom. The tracking 
approach compensates researcher observation by continuously capturing peer social contact 
across classroom activities and context. For the present purposes, we will use a Bluetooth-based 
identification and proximity detection system for a six-hour period on 8-16 rendomly selected 
observation days throughout the year.  A bluetooth beacon and up to two audio recorders will be 
attached to a vest/pouch that will be worn by children and teachers participating in the study. A 
set of antennas located in the corners of the classroom will emit radio frequency signals, which 
will be detected by the tags in each participant vest/pouch. The tags will also communicate with 
other participants’ tags to measure proximity. Based on the patterns of emission and reception of 
these signals, the bluetooth system identifies and locates each participant in the classroom. The 
set of location tracks are be analyzed to determine instances and time durations of person-to-
person proximity (e.g., child near child, child near teacher). Based on the location information 
among children, a classroom social network will be created for each observation window.  

For the proposed study, researcher observations are executed on days these location recordings 
occur, so that we can not only triangulate the social network data, but also validate that social 
networks based on location tracking validly represent authentic forms of peer socialization. 
Based on each social network generated from either researcher observation or location tracking 
across the 8-16 timepoints, the social status of each child in the classroom network will be 
represented by two types of individual centrality indices: degree centrality (i.e., the amount of 
social interactions directly associated with a child) and eigenvector centrality (i.e., the amount of 
social interactions directly associated with a child and indirectly associated with the child 
through their peers, e.g., “friends’ friends”). Classroom network density is also calculated to 
represent the average interaction intensity in the classroom, with higher values representing a 
more closely connected classroom network.  
Focal Child Observations and Assessments  
Focal Child observations.  
Pilot Study: To ensure we are able to accurately capture this proximal treatment outcome 
during the main study, we examine focal children’s social interactions with classmates in terms 
of peer interactions and peer talk. These activities are conducted on the same day as the 
researcher observations and occur during weekly during weeks 2-5 of the pilot study.  For this 
observation, observers will observe the focal child for 30 minutes during center time and apply a 
partial interval recording system involving 15 s of observation and 15 s of documentation. Two 
variables are captured: (1) peer interactions and (2) play interactions. For peer interactions, each 
interval is coded for whether nonverbal or verbal interaction was directed to or from the focal 
child. These simply capture the extent to which focal children interact with peers in the 
classroom. For play interaction, each interval is coded for four possible categories of play: 
appropriate peer play, appropriate solitary play, inappropriate play, and no play. These 
observational data are derived to represent the percentage of intervals in which behaviors are 
coded. Reliability estimates are assessed for 20% of observations via double-coding. 
Main Study: As a proximal treatment outcome, we examine focal children’s social 
interactions with classmates in terms of peer interactions and peer talk. These activities are 
conducted on the same day as the researcher observations and occur 8-16 times annually (three at 
least 3 during intervention). For peer interactions, we observe the peer interactions of the focal 
children during observations conducted over the academic year using an established protocol 
(Brock et al., 2018). These are conducted on the same day as the prior observation (researcher 
observation), with order randomized. For this observation, observers will observe the focal child 
for 30 minutes during center time and apply a partial interval recording system involving 15 s of 
observation and 15 s of documentation. Two variables are captured: (1) peer interactions and (2) 
play interactions. For peer interactions, each interval is coded for whether nonverbal or verbal 
interaction was directed to or from the focal child. These simply capture the extent to which 
focal children interact with peers in the classroom. For play interaction, each interval is coded for 
four possible categories of play: appropriate peer play, appropriate solitary play, inappropriate 
play, and no play. These observational data are derived to represent the percentage of intervals in 

which behaviors are coded. Reliability estimates are assessed for 20% of observations via 
double-coding with observers blind to classroom and child condition. 
Peer Talk: For peer talk, we will record the amount of incoming and outgoing talk focal 
children experience using a hands-free voice-activated recorder worn by each child in the vest, 
with audio capture transcending the entire classroom day. Teachers follow a protocol for placing 
the vest on each child at the start and end of the day. With multiple hours of audio recorded per 
child, we will process these recordings to capture duration of outgoing/incoming talk with 
proximate peers using the following process: (i) augment the voice-recorder ability/voice 
detection/processing algorithms from the Matlab Audio Systems Toolbox  to determine if people 
are speaking, and how long they are speaking; and (ii) use 2D-proximity data from continuous 
location tracking to parse the audio tracks across time into the cases where there is simultaneous 
peer proximity and recorded voice (i.e., peer-to-peer talk for some duration of time that we can 
obtain from stamp data from proximity/audio recording). While our initial plan does not involve 
transcribing or otherwise capturing the quality of peer talk, we will pursue additional funds to 
analyze these audio data later. 
Activity: Main Study Only: The children’s and teacher’s vest will also house a small 
accelerometer as a motion sensor. The output of this sensor will be used to detect classroom 
activities such as running, sitting, and sleeping.  
The audio, proximity, and activity data will be processed using machine learning 
algorithms that will perform speech annotation, speaker diarization and analyzed for word count 
estimates, automatic transcriptions, sentiment analysis, and classification of the nature of the 
interactions, including automatic identification of child-directed speech. Some of these programs 
require pre-trained machine-learning models housed in the OSU-configured cloud-computing 
provider Amazon Web Services (AWS), i.e., the computations are carried out in AWS servers, 
while the data remains accessible only to OSU project staff. 
Focal Child assessments.  
Pilot Study: We examine focal children’s language skills.  For language skills, we use the 
teacher DPP and PLRS and parent report DPP at pre- during week one of the pilot. 
Main Study: We examine focal children’s social, behavioral, and language skills as 
potential mediated outcomes. Measures are administered at three time-points—fall, winter, and 
spring—of the academic year. All measures are administered using tablet-based devices for 
efficiency and real-time data processing.  For social and behavioral skills, we use the teacher-
report Teacher-Child Rating Scale (TCRS (Hightower et al., 1986)), a 32-item teacher-report 
instrument that captures children’s social, behavioral, and emotional competence. For the 
proposed study, we will use the behavior control items to assess children’s problem behaviors 
and the social competence items to capture three areas of interest: task orientation, assertiveness, 
and peer social skills. Teachers respond to statements on a 5-point scale (1 = strongly disagree, 5 
= strongly agree) to describe each child in relation to these descriptions. This tool is easy and 
inexpensive to administer and yields psychometrically valid outputs on children’s social and 
behavior issues that are applicable to children with disabilities in inclusive classrooms (Juvonen 

& Bear, 1992). For language skills, we use the Developmental Pragmatic Profile (DPP) (Wiig et 
al., 2004), which is administered on each child in the classroom in the fall and spring (in 
accordance with the approved/signed infrormed consent materials), but to focal children again in 
winter. We examine change on each of three sub-scales: nonverbal skills; conversational skills; 
and asking for, giving, and responding to information. Teachers rate the child linguistic-
pragmatic skills on a 4-point scale for each of 26 items. Also, we administer one subtest of the 
Preschool Language Screener-5 Assessment: expressive language (Zimmerman et al., 2011). We 
will explore avenues for data reduction, including use of a latent-variable modeling strategy. The 
benefit of using this measure is that we have used it in extensive prior studies of similar samples 
and contexts, thus permitting us to explore study findings in relation to considerably larger 
samples of children with LI (Justice et al., 2014a) and their approximate annual language growth. 
Descriptives and possible covariates  
Pilot: Teachers: Teachers will complete a survey prior to the pilot and provide demographics.  
The survey will also include the peer matrix and 5 questions about past social supports and 
experience with peer-mediated interventions.  During week 6 of the pilot, teachers will complete 
an 8 item questionnaire to provide information on the feasibility and tolerance of implementing 
the pilot intervention in their classrooms; Parents: will complete an IFQ with their consent form 
to determine eligibility.  Caregivers of peers and target children will be asked to complete one 
survey during the pilot, which will collect the following information: demographics, household 
socioeconomic status (caregiver education levels), a set of 5 items to capture child social 
network information; the DPP.  Only focal child and peer parents who will complete the survey 
during the pilot.  
Peer and target children will be asked to complete a brief 4 minute interview during weeks 1 and 
6 of the pilot. 
Main Study: Descriptives and potential covariates to be captured and explored in analyses 
include (1) classmates’ language skills (fall and spring DPP completed for each child by 
teacher), (2) classroom composition characteristics including percentage of children with 
disabilities, gender, and age (provided by teachers in fall), and (3) focal child sociodemographic 
factors. For the latter, we collect a questionnaire from the primary caregiver in the fall and spring 
(in accordance with the approved/signed infrormed consent materials) to assess household 
socioeconomic status (caregiver education levels and employment status, household 
composition, and transience—including whether or not the family experienced a serious family 
event over the last school year to be answered in spring), home literacy activities per established 
protocols (Justice, Logan, Işıtan, & Saçkes, 2016), and child language history. 
e. Confidentiality of Data 
Any data collected will be de-identified to maintain confidentiality. Any participants will be 
assigned a subject ID. Subject IDs and names will be separated. All data will be stored in a 
locked cabinet. Audio, proximity, activity, observation and questionnaire record data will be 
downloaded to a password-protected computer. Only study personnel will have access to this 
data. Segments of audio, proximity, and activity data will be processed in the cloud using OSU-

configured cloud-computing service, which provide in-transit and in-use encryption of data. 
OSU will serve as the central data hub and the IRB of record for all study activities. 
f. Internal Validity 
Standardized procedures of all instrumentation will be utilized to ensure proper administration 
g. Data Analysis 
Aim 1 investigates the effects of peer-mediated PRT on the peer interactions and social 
status (indicated by individual centrality) within the classroom social network for children with 
LI. We assess this aim based on 6 to 24 repeated measurements for each outcome variable using 
multilevel growth models (Raudenbush & Bryk, 2002) to investigate changes in key outcomes 
over the school year and to accommodate the wait-list experimental design. Longitudinal 
measurements will be nested within participants and predicted by the time of measurement as 
well as time-specific intervention status. We include interaction terms between time of 
measurement and intervention status so that any accelerating or decelerating effects of 
intervention can be captured. In all models, we control for relevant covariates to increase 
precision of parameter estimates and power (Hox, Moerbeek, & Van de Schoot, 2010; 
Raudenbush, Martinez, & Spybrook, 2007). To assess treatment effects on peer interactions, we 
use the number of peer interaction, number of appropriate peer play, and duration of peer talk for 
the focal children as the outcome variables in the growth models. Depending on the distribution 
of the variables, appropriate linear or generalized linear models (e.g., Poisson) will be fitted. To 
examine treatment effects on social status, we compare the trajectories of individual centrality 
for the focal children and their classmates, controlling for classroom-level variation. Specifically, 
intervention effects are tested on key components of the trajectories, such as intercept, linear 
slope and quadratic slope (i.e., the slowing or acceleration of growth). The growth curves for 
different groups (treatment, wait-list control, and peer) can then be estimated. Aim 2 determines 
the extent to which peer-mediated PRT contributes to focal children’s social, behavioral, and 
linguistic skills via the mediation of improved socialization experiences. For this aim, we employ 
multivariate latent growth models, where latent growth curves of socialization indices and child 
skills can be modelled simultaneously and the relationships between latent growth parameters 
examined. In particular, two latent slopes (fall and spring) will be specified for the socialization 
growth curve to capture the differential growth rate with and without intervention; intervention 
status will be used as a predictor of the two socialization slopes. Due to the sample size 
limitation, we will examine one socialization index and one skill variable at a time. We will 
focus on the following pathways: (a) effect of intervention on focal children’s socialization 
experiences at fall, winter, and spring; and (b) effects of socialization experiences on child skills 
at fall, winter, and spring. Paths (a)*(b) allow us to test the indirect effects of PRT on social, 
behavioral, and linguistic skills. To estimate the mediation effect, we use the product-of-
coefficient approach (MacKinnon, Lockwood, Hoffman, West, & Sheets, 2002) with a 
bootstrapping procedure (Preacher & Hayes, 2004, 2008). This method does not require the 
assumption of normality for the sampling distribution of the product-of-coefficient. Finally, Aim 
3 examines changes in classroom social network dynamics over the school year, and tests the 
effects of peer-mediated PRT on peer socialization at the classroom level. To address this aim, 

we adopt multilevel growth models similar to those described in Aim 1, except with classroom-
level social network indices as outcomes and classrooms as the level-2 unit of analysis. With 
repeated measurements across the school year, the change rates in socialization indices can be 
estimated for and compared between the intervention period and control period.   
 
IV. 
Bibliography 
Brock, M. E., Dueker, S. A., & Barczak, M. A. (2018). Brief Report: Improving Social 
Outcomes for Students with Autism at Recess Through Peer-Mediated Pivotal Response 
Training. Journal of Autism and Developmental Disorders, 48(6), 2224–2230. 
https://doi.org/10.1007/s10803-017-3435-3 
Buhs, E. S., & Ladd, G. W. (2001). Peer rejection as an antecedent of young children’s school 
adjustment: an examination of mediating processes. Developmental Psychology, 37(4), 
550–560. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/11444490 
Bulotsky-Shearer, R. J., Manz, P. H., Mendez, J. L., McWayne, C. M., Sekino, Y., & Fantuzzo, 
J. W. (2012). Peer Play Interactions and Readiness to Learn: A Protective Influence for 
African American Preschool Children From Low-Income Households. Child Development 
Perspectives, 6(3), 225–231. https://doi.org/10.1111/j.1750-8606.2011.00221.x 
Chen, J., Lin, T.-J., Justice, L., & Sawyer, B. (2019). The Social Networks of Children With and 
Without Disabilities in Early Childhood Special Education Classrooms. Journal of Autism 
and Developmental Disorders, 49(7), 2779–2794. https://doi.org/10.1007/s10803-017-
3272-4 
Conti-Ramsden, G., & Botting, N. (2004). Social Difficulties and Victimization in Children With 
SLI at 11 Years of Age. Journal of Speech, Language, and Hearing Research, 47(1), 145–
161. https://doi.org/10.1044/1092-4388(2004/013) 
Fantuzzo, J., Sekino, Y., & Cohen, H. L. (2004). An examination of the contributions of 
interactive peer play to salient classroom competencies for urban head start children. 
Psychology in the Schools, 41(3), 323–336. https://doi.org/10.1002/pits.10162 
Hightower, A. D., Work, W. C., Cowen, E. L., Lotyczewski, B. S., Spinell, A. P., Guare, J. C., & 
Rohrbeck, C. A. (1986). The Teacher-Child Rating Scale: A brief objective measure of 
elementary children’s school problem behaviors and competencies. School Psychology 
Review, 15(3), 393–409. 
Hox, J. J., Moerbeek, M., & Van de Schoot, R. (2010). Multilevel analysis: Techniques and 
applications. Routledge. 
Justice, L. M., Ahn, W.-Y., & Logan, J. A. R. (2019). Identifying Children With Clinical 
Language Disorder: An Application of Machine-Learning Classification. Journal of 
Learning Disabilities, 52(5), 351–365. https://doi.org/10.1177/0022219419845070 
Justice, L. M., Chen, J., Jiang, H., Tambyraja, S., & Logan, J. (2019). Early-Literacy 
Intervention Conducted by Caregivers of Children with Language Impairment: 
Implementation Patterns Using Survival Analysis. Journal of Autism and Developmental 

Disorders. https://doi.org/10.1007/s10803-019-03925-1 
Justice, L. M., Logan, J. A. R., Işıtan, S., & Saçkes, M. (2016). The home-literacy environment 
of young children with disabilities. Early Childhood Research Quarterly, 37, 131–139. 
https://doi.org/10.1016/j.ecresq.2016.05.002 
Justice, L. M., Logan, J. A. R., Lin, T.-J., & Kaderavek, J. N. (2014a). Peer Effects in Early 
Childhood Education. Psychological Science, 25(9), 1722–1729. 
https://doi.org/10.1177/0956797614538978 
Justice, L. M., Logan, J. A. R., Lin, T. J., & Kaderavek, J. N. (2014b). Peer Effects in Early 
Childhood Education: Testing the Assumptions of Special-Education Inclusion. 
Psychological Science, 25(9), 1722–1729. https://doi.org/10.1177/0956797614538978 
Juvonen, J., & Bear, G. (1992). Social adjustment of children with and without learning 
disabilities in integrated classrooms. Journal of Educational Psychology, 84(3), 322–330. 
https://doi.org/10.1037/0022-0663.84.3.322 
Longobardi, E., Spataro, P., Frigerio, A., & Rescorla, L. (2016). Language and social 
competence in typically developing children and late talkers between 18 and 35 months of 
age. Early Child Development and Care, 186(3), 436–452. 
https://doi.org/10.1080/03004430.2015.1039529 
MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V. (2002). A 
comparison of methods to test mediation and other intervening variable effects. 
Psychological Methods, 7(1), 83–104. https://doi.org/10.1037/1082-989X.7.1.83 
Nakamoto, J., & Schwartz, D. (2010). Is Peer Victimization Associated with Academic 
Achievement? A Meta-analytic Review. Social Development, 19(2), 221–242. 
https://doi.org/10.1111/j.1467-9507.2009.00539.x 
Preacher, K. J., & Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects 
in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4), 
717–731. https://doi.org/10.3758/BF03206553 
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and 
comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 
879–891. https://doi.org/10.3758/BRM.40.3.879 
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data 
analysis methods (Vol. 1). sage. 
Raudenbush, S. W., Martinez, A., & Spybrook, J. (2007). Strategies for Improving Precision in 
Group-Randomized Experiments. Educational Evaluation and Policy Analysis, 29(1), 5–29. 
https://doi.org/10.3102/0162373707299460 
Schaefer, D. R., Light, J. M., Fabes, R. A., Hanish, L. D., & Martin, C. L. (2010). Fundamental 
principles of network formation among preschool children. Social Networks, 32(1), 61–71. 
https://doi.org/10.1016/j.socnet.2009.04.003 
Wiig, E., Secord, W., & Semel, E. (2004). CELF preschool 2: clinical evaluation of language 
fundamentals preschool. Pearson/PsychCorp.