BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//conferences.acspri.org.au//2024//speaker//S8QKKM
BEGIN:VTIMEZONE
TZID:AEST
BEGIN:STANDARD
DTSTART:20000326T040000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3;UNTIL=20050326T170000Z
TZNAME:AEST
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
END:STANDARD
BEGIN:STANDARD
DTSTART:20060402T040000
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=4;UNTIL=20060401T170000Z
TZNAME:AEST
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
END:STANDARD
BEGIN:STANDARD
DTSTART:20070325T040000
RRULE:FREQ=YEARLY;BYDAY=4SU;BYMONTH=3;UNTIL=20070324T170000Z
TZNAME:AEST
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
END:STANDARD
BEGIN:STANDARD
DTSTART:20080406T040000
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=4
TZNAME:AEST
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20000827T030000
RRULE:FREQ=YEARLY;BYDAY=4SU;BYMONTH=8;UNTIL=20000826T170000Z
TZNAME:AEDT
TZOFFSETFROM:+1000
TZOFFSETTO:+1100
END:DAYLIGHT
BEGIN:DAYLIGHT
DTSTART:20011028T030000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10;UNTIL=20071027T170000Z
TZNAME:AEDT
TZOFFSETFROM:+1000
TZOFFSETTO:+1100
END:DAYLIGHT
BEGIN:DAYLIGHT
DTSTART:20081005T030000
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=10
TZNAME:AEDT
TZOFFSETFROM:+1000
TZOFFSETTO:+1100
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:pretalx-2024-NWGKZ9@conferences.acspri.org.au
DTSTART;TZID=AEST:20241129T091500
DTEND;TZID=AEST:20241129T093000
DESCRIPTION:Surveys are an important tool in social studies\, and most surv
 eys require respondents to rate items on a Likert scale. In this sense\, t
 he data collected are often ordinal in nature. This very nature poses chal
 lenges to data analysis\, as many statistical techniques become inappropri
 ate. In this presentation\, a parsimonious mixture distribution\, called t
 he combination of uniform and binomial (CUB)\, which is specifically built
  for ordinal data\, will be revisited. Under CUB\, each response is assume
 d to originate from either the respondent's uncertainty or the actual feel
 ing towards the survey item. In other words\, the CUB model can account fo
 r respondents' hesitation or indecisiveness towards the survey question\, 
 making it a powerful tool to capture the extra variabilities inherent in t
 he responses.\n\nSince most surveys contain more than one question\, the d
 ata collected are multivariate in nature\, and the associations between di
 fferent survey items are usually of considerable interest. An extension of
  the univariate CUB model to the bivariate case will be introduced. Most o
 f the previous attempts employed the method of copula\, which makes interp
 retation difficult. In the opposite\, our proposed method bypasses the use
  of copula and allows the associations between the unobserved uncertainty 
 and feeling components of the responses to be estimated. This distinctive 
 feature makes our proposed model more interpretable compared to copula-bas
 ed ones.  In addition\, the model parameters can be shown to be identifiab
 le\, making the model statistically valid.\n\nSuch a bivariate CUB model c
 an serve as a tool for analysing survey data in social sciences and other 
 disciplines. This presentation will describe the underlying logic and both
  theoretical and practical aspects of the proposed model\, and will demons
 trate its application through a real-word example.
DTSTAMP:20260912T202845Z
LOCATION:Sutherland Room
SUMMARY:A multivariate mixture distribution for modelling survey data - Rya
 n Ip\, Ka Yui Karl Wu
URL:https://conferences.acspri.org.au/2024/talk/NWGKZ9/
END:VEVENT
END:VCALENDAR