A decision tree approach to selecting an appropriate observation reliability index

Based on the conceptual framework outlined by Cone (1986) and Suen (1988), a practical decision tree is developed as an aid for the selection of observational reliability indices.     

Some empirical justification for a modest proposal regarding data acquisition via intermittent direct observation

Computer simulations of behavior and event records of a child's visual fixation on an adult person were generated and sampled using a modified time sampling procedure. The modified approach required making two independent scoring judgments per observation interval: if the behavior was initiated within the interval, the interval was scored; if the behavior was ongoing precisely at the end of the interval, the interval was again scored. The results showed that the within-interval and end-of-interval scores yielded, respectively, estimates of behavioral frequency and duration. The accuracy of the estimates was a function of the number of observations. Several field studies demonstrated high agreement among observers who employed the measurement system.     

Multidimensional rotation and scaling of configurations to optimal agreement

An integrated method for rotating and rescaling a set of configurations to optimal agreement in subspaces of varying dimensionalities is developed. The approach relates existing orthogonal rotation techniques as special cases within a general framework based on a partition of variation which provides convenient measures of agreement. In addition to the well-known Procrustes and inner product optimality criteria, a criterion which maximizes the consensus among subspaces of the configurations is suggested. Since agreement of subspaces of the configurations can be examined and compared, rotation and rescaling is extended from a data transformation technique to an analytical method.     

A cautionary note on the use of probability values to evaluate interobserver agreement

Proposed methods of assessing the statistical significance of interobserver agreements provide erroneous probability values when conducted on serially correlated data. Investigators who wish to evaluate interobserver agreements by means of statistical significance can do so by limiting the analysis to every k(th) interval of data, or by using Markovian techniques which accommodate serial correlations.     

Measures of observer agreement when binomial data are collected in free operant situations

This paper examines a model and defines reasonable assumptions underlying different measures of observer agreement for categorical data collected in free operant situations. It is assumed that two or more observers classify operant behaviors of subjects into occurrences and nonoccurrences by recognition by validated response classes (categories) such that the rates of false positives and observer biases are acceptably low. Thus errors are mostly omissions, i.e., failing to observe events that occur. Four alternative cases are derived, together with formulas for calculating significance tests, variances, and standard errors, three of which do not depend on knowledge of the proportion of time points at which the event does not occur.We wish to acknowledge NICHD Grant HD-10570, The Neuropharmacology of Developmental Disorders, George Breese, Ph.D., and C. T. Gualtieri, M.D., Principal Investigators; NIEHS Grant ES-01104; USPHS Grant HD-03110; and MCH Project 916 to the Division for Disorders of Development and Learning.     

Youth-parent consistencies on ratings of difficulties and prosocial behavior: exploration of an at-risk sample

Low informant agreement is of particular concern in clinical settings, since diagnoses and interventions are largely based on reports from parents and/or youths. This study explores youth-parent consistencies in an at-risk sample of youths (n = 42), several from immigrant and refugee families, all with stressful background experiences. Data from a community sample (n = 165) was used to contrast the clinical results. Results showed that correlations between clinical youths and parents were within the same range as those in the community sample. Consistencies concerning absolute level of behavior were higher in the clinical sample. However, interesting differences in informant consistencies were found on difficulties and resources between the two samples. This study adds to the picture that there is no simple relationship between severity of behavior deviance and informant agreement. Asking about behavioral resources as well as difficulties may provide valuable additional information regarding differences in the perspectives of at-risk youths and parents.     

Reliability in the context of the experiment: A commentary on two articles by Birkimer and Brown

Two sources of variability must each be considered when examining change in level between two sets of data obtained by human observers; namely, variance within data sets (phases) and variability attributed to each data point (reliability). Birkimer and Brown (1979a, 1979b) have suggested that both chance levels and disagreement bands be considered in examining observer reliability and have made both methods more accessible to researchers. By clarifying and extending Birkimer and Brown's papers, a system is developed using observer agreement to determine the data point variability and thus to check the adequacy of obtained data within the experimental context.     

A graphical judgmental aid which summarizes obtained and chance reliability data and helps assess the believability of experimental effects

Interval by interval reliability has been criticized for "inflating" observer agreement when target behavior rates are very low or very high. Scored interval reliability and its converse, unscored interval reliability, however, vary as target behavior rates vary when observer disagreement rates are constant. These problems, along with the existence of "chance" values of each reliability which also vary as a function of response rate, may cause researchers and consumers difficulty in interpreting observer agreement measures. Because each of these reliabilities essentially compares observer disagreements to a different base, it is suggested that the disagreement rate itself be the first measure of agreement examined, and its magnitude relative to occurrence and to nonoccurrence agreements then be considered. This is easily done via a graphic presentation of the disagreement range as a bandwidth around reported rates of target behavior. Such a graphic presentation summarizes all the information collected during reliability assessments and permits visual determination of each of the three reliabilities. In addition, graphing the "chance" disagreement range around the bandwidth permits easy determination of whether or not true observer agreement has likely been demonstrated. Finally, the limits of the disagreement bandwidth help assess the believability of claimed experimental effects: those leaving no overlap between disagreement ranges are probably believable, others are not.     

A method for combining occurrence and nonoccurrence interobserver agreement scores

Various statistics have been proposed as standard methods for calculating and reporting interobserver agreement scores. The advantages and disadvantages of each have been discussed in this journal recently but without resolution. A formula is presented that combines separate measures of occurrence and nonoccurrence percentages of agreement, with weight assigned to each measure, varying according to the observed rate of behavior. This formula, which is a modification of a formula proposed by Clement (1976), appears to reduce distortions due to "chance" agreement encountered with very high or low observed rates of behavior while maintaining the mathematical and conceptual simplicity of the conventional method for calculating occurrence and nonoccurrence agreement.