BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Makerere University College of Business and Management Sciences - ECPv6.15.18//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://bams.mak.ac.ug
X-WR-CALDESC:Events for Makerere University College of Business and Management Sciences
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:UTC
BEGIN:STANDARD
TZOFFSETFROM:+0000
TZOFFSETTO:+0000
TZNAME:UTC
DTSTART:20240101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=UTC:20251218T140000
DTEND;TZID=UTC:20251218T170000
DTSTAMP:20260404T095115
CREATED:20251215T085936Z
LAST-MODIFIED:20251215T090201Z
UID:11644-1766066400-1766077200@bams.mak.ac.ug
SUMMARY:PhD Public Defense by Mr. Hillary Muhanguzi
DESCRIPTION:INVITATION: \nThe Dean\, School of Statistics and Planning under the College of Business and Management Sciences (CoBAMS)\, cordially invites you to the PhD Public Defense of the following candidate: \nName of the Candidate: Mr. Hillary Muhanguzi \n Title of Thesis: \nMethodological aspects in the construction of a composite indicator of service delivery in Uganda \n Date:    Thursday 18th  December 2025. \nTime:   2:00pm – 5:00pm \nVenue:   School of Statistics Board Room A16 \n  \nABSTRACT \n This study elaborates methodological aspects encountered in the building of composite indicators with application to service delivery in Uganda. This study amplified the three main stages\, the selection of quality data\, the building of the composite indicator itself and statistical approaches that may be utilized to model service delivery composite indicator (CI). This study formulated a data quality assessment framework (DQAF) to enhance the construction of a composite indicator. The DQAF was formulated with a dual orientation that prioritizes two user-oriented data quality components (DQCs) namely; relevance\, and interpretability\, and three producer-oriented DQCs of methodological soundness\, accuracy\, and statistical adequacy. The application of the DQAF to service delivery data resulted in the selection of 51 from a pool of 103 potential indicators\, reflecting a 48.6% acceptability percentage. The composite indicator for statistical regions\, which included five dimensions—education\, health\, water\, agriculture\, and roads—was developed utilizing official data from the 2021 National Service Delivery Survey conducted by the Uganda Bureau of Statistics\, along with various sector performance reports from the Ministry of Health and the Ministry of Water and Environment. Additionally\, the study developed an alternative composite indicator for district local governments\, concentrating on the education\, health\, and water dimensions\, which was modeled against potential covariates. The composite indicator for statistical regions indicated that Uganda achieved a score of 0.49 (0 ≤ composite indicator score ≤ 1) utilizing equal weighting\, minimax transformation\, and additive aggregation\, whereas the score was 0.45 with equal weighting\, distance-to-reference point transformation\, and geometric aggregation. Min-max transformation yields higher scores compared to distance-to-reference point\, attributable to the exogenously determined goalposts. Weights that are participatory determined were comparable with data-derived weights. Robustness tests demonstrated that the constructed composite indicator exhibited stability and can therefore be utilized. The absolute differences in ranks by region were observed\, with Kampala and Lango exhibiting the lowest differences and Karamoja and Kigezi the highest\, attributable to the presence of outliers and inequitable performance in the examined variables. The aggregation stage was the most sensitive accounting for nearly 60% of the total variance\, primarily due to interaction with mainly the transformation stage; this underscores the necessity to cautiously select an aggregation method\, as it greatly influences the robustness of the results. \nThe absolute rank differences were highest in the education dimension at 2.00 and lowest in the roads and health dimension at 1.33\, indicating the varying impact of excluding aspects from the composite index. In assessing the differentials of service delivery at local government level\, the composite indicator scores ranged from 0.25 to 0.60\, with a substantial portion of the density plot situated below 0.50\, indicating inadequate service delivery levels. The scores were negatively influenced by the number of sub-counties and land area\, and positively influenced by central government funding\, funding from other agencies\, number of town councils\, and age of the district. While beta regression adeptly models bounded data\, random forest regression highlights the relative importance of predictors\, and generalized additive model captures non-linear covariate effects. The comparable predictive accuracy of these methods\, as evaluated using root mean square error\, suggests their applicability to this investigation in accordance with the analytical objectives. A dual orientation of data quality components should be developed collaboratively\, ensuring that redundancies and overlaps are recognized and resolved to clarify the intrinsic qualities of data and elementary indicators. Furthermore\, it is recommended to investigate penalization methods to manage the substitutability of variables during aggregation due to unequal performance\, as well as to employ both parametric and non-parametric techniques to assess differentials in service delivery. \nSupervisors: \n\n Yeko Mwanga\n James.Wokadala\n Francesca Bassi\n Muuela Scioni\n\nYour presence and participation will be highly appreciated as we support the student in this important academic milestone. \n 
URL:https://bams.mak.ac.ug/event/phd-public-defense-by-mr-hillary-muhanguzi/
LOCATION:School of Statistics BoardRoom\, Makerere University
CATEGORIES:University-Wide
ATTACH;FMTTYPE=image/jpeg:https://bams.mak.ac.ug/wp-content/uploads/2025/12/photo.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260211T100000
DTEND;TZID=UTC:20260211T130000
DTSTAMP:20260404T095115
CREATED:20260204T110134Z
LAST-MODIFIED:20260204T110710Z
UID:11762-1770804000-1770814800@bams.mak.ac.ug
SUMMARY:PhD Public Defense for Ms. Lillian Ayebale
DESCRIPTION:INVITATION: \nThe Dean\, School of Statistic and Population Studies  under the College of Business  and Management Sciences  (CoBAMS)\, cordially invites you to the PhD Public Defense of the following candidate: \nName of the Candidate: Ms. Lillian Ayebale  \nTitle of Thesis: \nRisky Sexual Behaviours\, fertility and coping responses among adolescents in South- central Uganda \n Date:  Wednesday 11th  Februrary  2026. \nTime: 10:00am – 1:00pm \nVenue: \nSchool of Statistics Board Room \nABSTRACT \nAdolescents in Uganda face multiple vulnerabilities and exposures to risks. Approximately 25% of Ugandan teenagers become pregnant by the age of 19 years. This study explored and examined risky sexual behaviors\, fertility\, and coping responses among adolescents in South-Central Uganda. \nThis was a mixed-methods study. It involved a systematic review of studies on correlates of fertility among adolescents in SSA\, statistical analysis of risky sexual behaviors among adolescents\, and qualitative interviews with adolescents and parents from the Rakai Community Cohort Study (RCCS)\, a population-based HIV surveillance cohort. A systematic review protocol was developed and published in PROSPERO to guide the systematic synthesis of determinants of adolescent fertility in SSA. A negative binomial regression model was used to determine the risky sexual behaviours among adolescents\, while the qualitative data analysis adopted an interpretivist approach to understand risky sexual behaviors and how parents influence these adolescent behaviors. \nCultural practices and taboos\, child marriages\, lack of parent-child communication on sexual matters\, socioeconomic factors\, and adolescent individual factors were consistently cited as key correlates of adolescent fertility according to the systematic synthesis. Adolescents aged 18-19 exhibited a significantly higher incidence of risky sexual behaviours compared to those aged 15-17 (aIRR = 2.01\, 95% CI: 1.77-2.28). Living in a single-mother family structure (aIRR = 1.36\, 95% CI: 1.15-1.60)\, with other relatives (aIRR = 1.34\, 95% CI: 1.12-1.60)\, with non-relatives (aIRR = 1.53\, 95% CI: 1.21-1.94)\, or alone (adolescent-headed) (aIRR = 1.68\, 95% CI: 1.34-2.10) were all associated with higher incidence rates compared to living with both biological parents. Parents acknowledged that talking with adolescents could help reduce risky sexual behaviour. Parental talks on sexual matters were usually unplanned and happened when triggered by specific incidents. \nEvidence from the results suggest that adolescents engage in risky sexual behaviours including non-marital sexual partnerships\, multiple sexual partners\, unprotected sex with a non-marital partner\, and transactional sex. Parent-adolescent communication on sexual matters is essential/pertinent approach is needed to reduce/avert the associated risks. There is need for continuous engagement of all different stakeholders involved in adolescents work to have targeted interventions to prevent the risky sexual behaviours among the young people. \n Supervisors: \n\nAllen Kabagenyi\nStephen Ojiambo Wandera\n\nCritical Reader: \nDr. John Ssekamate – Ssebuliba \nYour presence and participation will be highly appreciated as we support the student in this important academic milestone. \n 
URL:https://bams.mak.ac.ug/event/phd-public-defense-for-ms-lillian-ayebale/
LOCATION:School of Statistics Board Room\, Makerere University\, KAMPALA\, KAMPALA\, +2560414\, Uganda
CATEGORIES:PhD Defense
ATTACH;FMTTYPE=image/jpeg:https://bams.mak.ac.ug/wp-content/uploads/2026/02/Lilian_Ayebale.jpeg
END:VEVENT
END:VCALENDAR