# Modern Statistical Methods for HCIUsing R for Repeated and Time-Series Observations

Modern Statistical Methods for HCI: Using R for Repeated and Time-Series Observations [This chapter explores calculating two types of analyses that are often used for repeated measures designs: within-subjects Analysis of Variance (ANOVA) and Event History Analysis. Within-subjects ANOVA is used when members of a particular sample are exposed to several different conditions or experiments and the measurement of the dependent variable is repeated in each condition, thus inducing correlation between the set of dependent variable measurements for each individual. Event history analysis, by contrast, helps researchers to determine the probability that an event occurs at a particular time interval, making it useful for research questions that want to know how long it takes before the event of interest happens. Both of these analyses have particular relevance for the field of human-computer interaction and this chapter will explore how to use R for these two types of analyses using the Mango watch example.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

# Modern Statistical Methods for HCIUsing R for Repeated and Time-Series Observations

Part of the Human–Computer Interaction Series Book Series
Editors: Robertson, Judy; Kaptein, Maurits
22 pages

/lp/springer-journals/modern-statistical-methods-for-hci-using-r-for-repeated-and-time-uzoOw7GHmJ
Publisher
Springer International Publishing
© Springer International Publishing Switzerland 2016
ISBN
978-3-319-26631-2
Pages
111 –133
DOI
10.1007/978-3-319-26633-6_6
Publisher site
See Chapter on Publisher Site

### Abstract

[This chapter explores calculating two types of analyses that are often used for repeated measures designs: within-subjects Analysis of Variance (ANOVA) and Event History Analysis. Within-subjects ANOVA is used when members of a particular sample are exposed to several different conditions or experiments and the measurement of the dependent variable is repeated in each condition, thus inducing correlation between the set of dependent variable measurements for each individual. Event history analysis, by contrast, helps researchers to determine the probability that an event occurs at a particular time interval, making it useful for research questions that want to know how long it takes before the event of interest happens. Both of these analyses have particular relevance for the field of human-computer interaction and this chapter will explore how to use R for these two types of analyses using the Mango watch example.]

Published: Mar 23, 2016

Keywords: Within-Subjects ANOVA; Event History Analysis; Interest Happens; Dependent Variable Measurements; Repeated Measures ANOVA Design