By Patricia K. Kerig, Donald H. Baucom
A significant other quantity to relations Observational Coding platforms, this booklet strikes from the triad to the dyad and offers a show off for major advancements within the coding of intimate couple interactions. The desire is this booklet will give a contribution to the broadening and deepening of the sphere by way of disseminating info either concerning the coding platforms which were constructed, in addition to the conceptual and methodological concerns fascinated by couple observational study. the 1st 3 chapters current overviews of conceptual and methodological concerns within the learn of couple procedures. the remainder chapters describe contributions to the sphere by means of sixteen groups of researchers. each one bankruptcy offers information regarding the conceptual underpinnings and constitution of the coding process constructed by means of the authors and proof for its psychometric homes. Couple Observational Coding structures may be of curiosity to researchers learning couple interactions in addition to clinicians who paintings with undefined.
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Extra resources for Couple Observational Coding Systems
However, difficulties occur when the coders detect and code different events, so that either or both of the records contain additional codes that do not match the other record. When coder agreement is very high and such additional events are rare, the remaining pairs of codes may be easy to align. However, in other cases, sections of the coder records become misaligned in a way that makes it impossible to match pairs of codes. Even when the pairs are matched, it is unclear whether disagreements reflect instances in which the coders detected the same action but labeled it differently, which would be one coding disagreement, or instances in which each coder attended to a different action, and thus produced a different code, which would be counted as two coding disagreements.
After training is completed, the investigator continues to monitor agreement among the observers to detect observer drift so that corrective training can be conducted. Commonly, investigators monitor coder agreement on 20% to 25% of sessions evaluated by trained coders. For the purpose of monitoring coders, observer agreement should be assessed for whatever unit of behavior the coders record. For example, if the coders record content codes for specific events, then agreement should be assessed for the specific content codes.
Bakeman and Gottman (1997) argued that there is no standard by which to judge adequate levels of percent agreement because the interpretation of agreement is influenced by many factors, including the base rates for the behaviors. Nevertheless, for training purposes, it is useful to know that coders can agree on 80% to 90% of their coding decisions. However, for reporting purposes, percent agreement statistics should be supplemented with other indices that take into account base rates and chance agreement (Haynes & O'Brien, 2000).