To date, several data analysis methods have been used to estimate contingency strength, yet few studies have compared these methods directly. To compare the relative precision and sensitivity of four analysis methods (i.e., exhaustive event-based, nonexhaustive event-based, concurrent interval, concurrent+lag interval), we applied all methods to a simulated data set in which several response-dependent and response-independent schedules of reinforcement were programmed. We evaluated the degree to which contingency strength estimates produced from each method (a) corresponded with expected values for response-dependent schedules and (b) showed sensitivity to parametric manipulations of response-independent reinforcement. Results indicated both event-based methods produced contingency strength estimates that aligned with expected values for response-dependent schedules, but differed in sensitivity to response-independent reinforcement. The precision of interval-based methods varied by analysis method (concurrent vs. concurrent+lag) and schedule type (continuous vs. partial), and showed similar sensitivities to response-independent reinforcement. Recommendations and considerations for measuring contingencies are identified.

Children's vocal development occurs in the context of reciprocal exchanges with a communication partner who models "speechlike" productions. We propose a new measure of child vocal reciprocity, which we define as the degree to which an adult vocal response increases the probability of an immediately following child vocal response. Vocal reciprocity is likely to be associated with the speechlikeness of vocal communication in young children with autism spectrum disorder (ASD). Two studies were conducted to test the utility of the new measure. The first used simulated vocal samples with randomly sequenced child and adult vocalizations to test the accuracy of the proposed index of child vocal reciprocity. The second was an empirical study of 21 children with ASD who were preverbal or in the early stages of language development. Daylong vocal samples collected in the natural environment were computer analyzed to derive the proposed index of child vocal reciprocity, which was highly stable when derived from two daylong vocal samples and was associated with speechlikeness of vocal communication. This association was significant even when controlling for chance probability of child vocalizations to adult vocal responses, probability of adult vocalizations, or probability of child vocalizations. A valid measure of children's vocal reciprocity might eventually improve our ability to predict which children are on track to develop useful speech and/or are most likely to respond to language intervention. A link to a free, publicly-available software program to derive the new measure of child vocal reciprocity is provided. Autism Res 2018, 11: 903-915. © 2018 International Society for Autism Research, Wiley Periodicals, Inc.LAY SUMMARY:Children and adults often engage in back-and-forth vocal exchanges. The extent to which they do so is believed to support children's early speech and language development. Two studies tested a new measure of child vocal reciprocity using computer-generated and real-life vocal samples of young children with autism collected in natural settings. The results provide initial evidence of accuracy, test-retest reliability, and validity of the new measure of child vocal reciprocity. A sound measure of children's vocal reciprocity might improve our ability to predict which children are on track to develop useful speech and/or are most likely to respond to language intervention. A free, publicly-available software program and manuals are provided.

A simulation study that used 3,000 computer-generated event streams with known behavior rates, interval durations, and session durations was conducted to test whether the main and interaction effects of true rate and interval duration affect the error level of uncorrected and Poisson-transformed (i.e., corrected) count as estimated by partial-interval recording. For both count estimates, shorter intervals and lower true rates resulted in less error than longer intervals and higher rates. For all conditions tested, Poisson-corrected estimates were more accurate than uncorrected estimates. Therefore, using Poisson-corrected estimates and short intervals are recommended when partial-interval recording is used to estimate counts. Generality of results might be restricted to events that are about 1-s long. A URL was provided to aid in the computation of corrected counts.

A variety of sequential analysis methods exist to quantify close temporal associations between events from direct observation data. In the present study, we compared the relative accuracy and interpretability of five sequential-analysis methods using simulated data. The methods included three existing approaches (event lag, concurrent interval, and time window) and two proposed modifications of the event lag approach (event lag with contiguous pauses and event lag with noncontiguous pauses) designed to address limitations of the existing approaches. We evaluated accuracy on the basis of the extent to which the mean contingency estimates produced by each method approximated a known mean (i.e., zero). We evaluated interpretability on the basis of the extent to which the contingency estimates produced by each method were independent from chance estimates of the two-event sequence. The results indicated that the event lag with contiguous pauses method produced the most accurate and interpretable estimates of contingency. This modified method prevents the total number of event types from influencing contingency estimates, thus solving a problem associated with the traditional event lag method.

This study examined the sequential relationship between parent attentional cues and sustained attention to objects in young children with autism during a 20 min free-play interaction session. Twenty-five parent-child dyads with a preschool child with autism participated. Results indicated that (a) parent attentional cues that maintained the child's focus of attention were more likely to support child sustained object attention than parent attentional cues that redirected the child from his or her focus of attention or introduced a new focus of attention (d = 4.46), and (b) parent attentional cues that included three or more parent behaviors were more likely to support child sustained object attention than parent attentional cues that included one or two parent behaviors (d = 1.03).

In this article, we describe the Interval Manager (INTMAN) software system for collecting time-sampled observational data and present a preliminary application comparing the program with a traditional paper-and-pencil method. INTMAN is a computer-assisted alternative to traditional paper-and-pencil methods for collecting fixed interval time-sampled observational data. The INTMAN data collection software runs on Pocket PC handheld computers and includes a desktop application for Microsoft Windows that is used for data analysis. Standard analysis options include modified frequencies, percent of intervals, conditional probabilities, and kappa agreement matrices and values. INTMAN and a standardized paper-and-pencil method were compared under identical conditions on five dimensions: setup time, duration of data entry, duration of interobserver agreement calculations, accuracy, and cost. Overall, the computer-assisted program was a more efficient and accurate data collection system for time-sampled data than the traditional method.

Time-window sequential analyses test whether a target behavior occurs within a temporal window (e.g., within 2 seconds) after an antecedent behavior more than is expected by chance. This type of question is common when we need to know how one person or event may immediately affect another event or person in the natural environment. Theoretically, the significance of sequential associations from time-window analysis can be tested on the single subject level (Bakeman & Quera, 1995). The present Monte Carlo study was conducted to test the Type I error rates and the difference in sequential associations derived from four methods of time-window sequential analysis. The four methods vary according to whether they analyze the duration of antecedent and target behaviors. The results indicate that time-window sequential analysis method is generally valid. The results were most accurate when antecedent duration and target onset was analyzed. Although analyzing duration of the antecedent did affect the results, the effect size for the difference in results due to presence or absence of measuring duration of the antecedent was extremely small. Time-window analysis results appear unaffected by the decision to analyze the duration of the target event.

We present a new application of sampled permutation testing to examine whether two sequential associations are different within a single dyad (e.g., a teacher and a student). A Monte Carlo simulation with the same (i.e., 100 vs. 100) or a different (100 vs. 400) number of event pairs was used to simulate designs that use time-based (typicallyproducing equal-length comparisons) and event-based (typically producing different-length comparisons) data, respectively. For these pairs of simulated data streams, we compared the Type I error rates and the kappa for agreement on significance decisions, using the sampled permutation tests and the more traditional asymptotic log linear analysis. The results provide the first evidence relevant to evaluating the accuracy of log linear analysis and sampled permutation testing for the purpose of comparing sequential associations within a single dyad.

The purpose of this article is to outline the development of the Multiple Option Observation System for Experimental Studies (MOOSES), a flexible data collection package for applied behavioral research. Several data collection options are available to users of MOOSES. Event-based recording, interaction-based recording, duration recording, and interval recording are available to the users and can be used individually or together, depending upon the research question. The collection program can incorporate any of the keys on the keyboard. Function keys on the top or side are used for toggle (duration states) type data collection. Types of analysis include frequency and duration of discrete events, frequency of general behavior states, frequency and duration of events within behavioral states, percent interval analysis, sequential analysis, and interobserver agreement. Data obtained from MOOSES is easily incorporated with other data for further statistical analysis with standard statistical packages or popular spreadsheet programs. Applications of MOOSES and its uses in social interaction research are presented. Comparisons with other similar systems are provided.

PROCODER is a software system for observing and coding events that have been recorded on videotape. The system uses a personal-computer-based tape controller to control a VHS tape while observations are recorded. Frequencies of events, durations of events, and calculations of inter-observer agreement of events or intervals are included. Data can be output in ASCII format for use with other statistical programs. A sample study in which the system is used is described as well.

Portable electronic data collection devices permit investigators to collect large amounts of observational data in a form ready for computer analysis. These devices are particularly efficient for gathering continuous data on multiple behavior categories. We expect that the increasing availability of these devices will lead to greater use of continuous data collection methods in observational research. This paper addresses the difficulties encountered when calculating traditional interobserver agreement statistics for continuous, multiple-code scoring. Two alternative strategies are described that yield interobserver agreement values based on the exact time of behavior code entries by the primary and secondary observers.