Page 545 - Encyclopedia of Nursing Research
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512  n  TIME SERIES ANALYSIS



           They are appropriate to cyclical patterns as   response  patterns  of  individuals,  families,
           well as periodic or systematic variance across   communities, health care systems, or politi-
   T       time. Outcomes of nursing care are generally   cal institutions.
           quantified by measures of response changes   The characteristic feature of time series
           across  specified  periods  of  time:  improve-  analysis is that the phenomenon to be stud-
           ment or declines in health status, increase or   ied has a distinctive temporal component—
           decrease in strength or endurance are a few   the  behavioral  state  will  vary  predictably
           examples. Although these changes are often   with the passage of time. Obviously, the pas-
           treated  as  simple,  linear  processes,  the  rate   sage  of  time  cannot  be  manipulated,  thus,
           and  degree  of  linear  variation  in  outcome   differences  in  patterns  of  change  are  not  a
           variables  are  often  confounded  by  related   direct function of time. Instead, time is the
           or underlying predicable patterns of fluctu-  necessary temporal frame or marker in any
           ation,  Thus,  whereas  time  series  statistical   time  series  analysis  study.  Although  not
           models  are  an  appropriate  and  powerful   conceptually  an  independent  variable,  time
           methodology for analysis of intraindividual   assumes  that  role  in  univariate  time  series
           differences in predictable patterns of change,   statistical models. Time series studies can be
           they can also be used to identify recurring   either univariate or multivariate. However, a
           patterns  of  variation  that  are  confounding   time series variable always consists, by defi-
           the rate and degree of intervention success.  nition, of a series of observations that occur
              In  contrast  with  inferential  statistical   in  temporal  order.  Thus,  multivariate  time
           models, in which aggregate data are general-  series  analysis  is  accomplished  by  identify-
           ized to describe changes in human behavior,   ing the relationship between or among two
           time series analysis uses individual patterns   or more pairs of univariate time series.
           of  change  to  predict  future  behavior.  Thus,   unlike  inferential  statistical  models,
           the  subject  is  a  unitary  entity  or  system   time  series  data  points  are  not  intended  to
           whose behavioral state can be isolated within   be  independent  of  one  another.  Each  value
           a given point and measured through a speci-  is  highly  correlated  with  every  successive
           fied window of time. Allowing subjects to act   value. Thus, any observation in a time series
           as their own controls eliminates the random   has  significantly  less  individual  predictive
           heterogeneity  of  response  threat  to  infer-  significance than its inferential counterpart.
           ential  statistical  validity;  but  limits  statisti-  In  time  series  analysis,  predictive  power  is
           cal external validity. generalization of time   not a direct function of sample size. Instead,
           series findings requires repeated replications   predictive  power  depends  on  an  accurate
           in conceptually congruent others.        hypothesis of the internal temporal structure
              For the purpose of time series analysis,   of the phenomenon, selection of a sampling
           the singular system can be defined at many   time window of sufficient length to capture
           different  levels  of  complexity  and  inclu-  multiple  expressions  of  the  change  being
           siveness. However, because 50 observations   studied, and identification of a sampling fre-
           across the specified time period is the con-  quency that will adequately capture all criti-
           ventional  minimal  number  of  observations   cal phases of the evolving pattern.
           necessary  for  the  accurate  identification  of   Although change in behavior is an essen-
           predictable  patterns  of  behavior,  pragma-  tial characteristic of many of the phenomena
           tism  often  limits  subjects  for  time  series   of interest to nursing science, the use of statis-
           nursing  research  to  the  often  more  reliable   tical time series models is not always appro-
           physiological  and  directly  observed  behav-  priate  or  feasible.  However,  although  time
           iors  of  individuals,  for  example,  cardiovas-  series analyses are complex and costly, they
           cular responses to a cardiac stressor, rather   permit  nurse  scientists  to  more  completely
           than equally legitimate, social or behavioral   examine  and  evaluate  trends,  cycles,  and
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