trait. This is because a control group may necessarily be selected from a discrete separate population. This research design is thus considered a quasi-experimental design. Concurrent designs Multiple baseline studies are often categorized as either concurrent or nonconcurrent. Concurrent designs are the traditional approach to multiple baseline studies, where all participants undergo treatment simultaneously. This strategy is advantageous because it moderates several threats to validity, and history effects in particular. Concurrent multiple baseline designs are also useful for saving time, since all participants are processed at once. The ability to retrieve complete data sets within well defined time constraints is a valuable asset while planning research. Nonconcurrent designs Nonconcurrent multiple baseline studies apply treatment to several individuals at delayed intervals. This has the advantage of greater flexibility in recruitment of participants and testing location. For this reason, perhaps, nonconcurrent multiple baseline experiments are recommended for research in an educational setting. It is recommended that the experimenter selects time frames beforehand to avoid experimenter bias, but even when methods are used to improve validity, inferences may be weakened. Currently, there is debate as to whether nonconcurrent studies represent a real threat from history effects. It is generally agreed, however, that concurrent testing is more stable. Disadvantages Although multiple baseline experimental designs compensate for many of the issues inherent in ex post facto recruitment, experimental manipulation of a trait gathered by this method may not be manipulated. Thus these studies are prevented from inferring causation if there are no phases to demonstrate reversibility. However, if such phases are included (as is the standard of experimentation), they can successfully demonstrate causation. Managing threats to validity A priori (beforehand) specification of the hypothesis, time frames, and data limits help control threats due to experimenter bias. For the same reason researchers should avoid removing participants based on merit. Multiple probe designs may be useful in identifying extraneous factors which may be influencing your results. Lastly, experimenters should avoid gathering data during sessions alone. If in-session data is gathered a note of the dates should be tagged to each measurement in order to provide an accurate time-line for potential reviewers. This data may represent unnatural behaviour or states of mind, and must be considered carefully during interpretation. See also Single-subject design Single-subject research References External links http://allpsych.com/researchmethods/multiplebaselines.html https://www.msu.edu/user/sw/ssd/issd10d.htm http://findarticles.com/p/articles/mi_hb6516/is_4_41/ai_n29146430/ Design of experiments Quantitative research Psychological methodology Quantitative analysis of behavior