College of Natural and Computational Sciences

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    SURVIVAL ANALYSIS FOR HIV-TB CO-INFECTED PATIENTS UNDER ANTIRETROVIRAL THERAPY IN MEKELLE HOSPITAL AND AYDER COMPREHENSIVE REFERAL HOSPITAL TIGRAY, ETHIOPIA: APPLICATIONS OF A PARAMETRIC SHARED FRAILTY MODEL
    (Mekelle University, 2024-11-28) Tekleweyni Haftu
    Background: Human immunodeficiency virus (HIV) is an infection that attacks the body’s immune system. Acquired immunodeficiency syndrome (AIDS) is the most advanced stage of the disease. HIV remains one of the world's most significant public health challenges, particularly in low- and middle-income countries. Objectives: This study aimed to determine the potential risk factors affecting the time-to-death of HIV-TB co-infected patients in Mekelle and Ayder Comprehensive Referral hospitals and also demonstrate the application of parametric survival models in analyzing these survival outcomes. Methods: Parametric shared frailty models have been used with four baseline hazard functions (Exponential, Weibull, Log-logistic, Log-normal) and two frailty distributions (Gamma, InverseGaussian). 215 HIV-TB co-infected patients whose age was 18 and above who started ART from January 2015 to December 2016 and followed up to January 2020 were included in the study from Mekelle and Ayder hospitals. Data were analyzed using statistical software R version 4.4.1 and STATA version 14.0. Results: Out of 215 patients, about 60(28%) died while 155(72%) were censored during the follow-up period with the median death time of HIV-TB co-infected patients at 30 months. The clustering effect was significant, and the Weibull-Inverse Gaussian shared frailty model was preferred over the rest parametric shared frailty models based on the Akaike Information Criterion (AIC) and Bayesian Information Criteria (BIC). The result shows patients’ educational level, baseline Weight, TB type, baseline CD4, and place of residence were significant, whereas sex, WHO clinical stage, marital status, functional status, regimen type, and age were not significant covariates for HIV-TB co-infected patients in Mekelle and Ayder comprehensive Referral hospitals. The clustering effect was significant for modeling the time-to-death of HIV-TB patients’ dataset and there was heterogeneity among the hospitals on the death of patients (θ=040.). Conclusion: This study showed that there was a clustering (frailty) effect on modeling time to Death among patients treated in Mekelle and Ayder comprehensive hospitals because of heterogeneity in hospitals from which the patients are treated, assuming patients treated in the same hospital share similar risk factors related to death.
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    Analysis of Multi-environmental Trial Data Using AMMI and GGE Biplot on Barley Genotypes Evaluated in Tigray
    (Mekelle University, 2023-11-08) Tamrat Berhe
    Barley (Hordeum vulgare L.) was one of the first plants people grew for food, and now it's grown all over the world and it has a special role in Ethiopian agriculture. However, production is affected by environment interaction and lack of stable genotypes across locations. The presence of genotype-environment interaction (GEI) influences production making the selection of cultivars in a complex process. Since, this experiment were conducted for forty barley genotypes by Alpha lattice design using two replications at three locations in Tigray during 2017 and 2018 cropping seasons considering each year-location combination as a different environments. The study carried out with objectives to estimate magnitude of genotype by environment interaction, comparing AMMI and GGE to evaluate stability of genotypes and identifying superior genotypes. We observed significance effects in all sources of combined ANOVA, since the grain yields of all 40 barley genotypes were significantly affected by environment, which accounted for 40.6 % of the total variation, whereas genotype and genotypeenvironment interaction accounted for 21.12 % and 23.07 %, respectively. The two most used methods to analyze GEI and evaluate genotypes are AMMI and GGE Biplot, being used for the analysis of multi environment trials data (MET).Both models were equivalent for the data’s evaluation, but GGE permitting increased reliability in the selection of superior cultivars (Which-won-where pattern) and test environments (discrimitiveness vs. representativeness).Wricke’s ecovalence, Finley-Wilkinson, Shukla’s stability, Lin&Binns cultivar superiority measure, AMMI Stability Value (ASV), and YSI stability analysis measures also used to identify stable genotypes, and G19, G36, G5 are the most stable genotypes in almost the stability analysis measures, since they are superior genotypes with all test environments. While the genotypes G33, G32, G12 and G18 also the instable genotypes in the test environments. GGE Biplot view of relation among test environments of this study showed that; Among the testing environments Hagereselam 2018 is an ideal testing location to identify stable and high yielding genotypes followed by Ayba 2018, since Hagereselam 2018 and Ayba 2018 are most applicable test locations for identifying stable and high yielding barley genotypes for the region. Mean performance and stability of GGE biplot indicated that G24 had the ideal genotype with highest mean yield as well as stability with desirable genotypes G20, G19, G5, G36, while G33 and G30 had the lowest mean yield and less stability genotypes in all the six test environments.
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    SPATIAL DISTRIBUTION AND DETERMINANTS OF ANAEMIA AMONG WOMEN OF REPRODUCTIVE AGE IN ETHIOPIA USING MIXED-EFFECT ORDINAL LOGISTIC REGRESSION MODEL
    (Mekelle University, 2024-12-28) Solomon Tekeste
    Background: Anaemia is a condition characterized by a low blood hemoglobin concentration (120 g/L in non-pregnant women and below 110 g/L in pregnant women). It primarily affects women of reproductive age (WRA) and who suffer from anaemia has experienced detrimental effects on their mental development and future social functioning. Objectives: This study aimed to assess the spatial distribution and determinants of anaemia among women of reproductive age in Ethiopia. Methods: The study participants were all the WRA who were confirmed to anaemia from the 2019 EMDHS data source. The survey considered 8885 WRA; of which 1483 severe, 534 moderate, 1778 mild and 5090 none anaemia levels were included in this study. The study variable was defined as the ordinal level of anaemia (none, mild, moderate and severe) based on the WHO cut-off points. In this study, Moran’s-I, was used to investigate the presence of spatial autocorrelation. A mixed effect ordinal logistic regression model used allowed to analyze random and fixed effects of some covariates, spatial effects, and other fixed covariates. Inference used a full GLMM and several methods can be used to assess the goodness of fit in GLMMs, including the AIC and BIC techniques. Results: Out of 8885 WRA; included in this study 1483(16.7%) were found at a severe level of anemic. Due to the BIC model selection criteria, the GLMM model was found to be appropriate. From the model Individual factors (age group, religion, wealth index and marital status) and community factors (cooking fuel type, number of children, access to electricity, and having refrigerators) are found to be determinants, significant determinants of anaemia status among WRA and the spatial analysis demonstrated a clustered pattern of anaemia distribution, confirmed by the global Moran's I statistic (0.146652, p-value < 0.001). Conclusion: The finding revealed a spatial variation of anaemia status among WRA across the regions of Ethiopia with higher prevalence in the eastern parts of the country specifically in Somali and Harari regions. The application of the GLMM provided a more detailed understanding of the factors influencing anaemia status.
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    Statistical Analysis of Multi Environment Trials on Durum Wheat: The Use of AMMI and Stability Indices to Model Genotype by Environment Interaction
    (Mekelle University, 2023-11-28) Shshaye Hailu
    Background: Durum wheat is one of the most important crops worldwide with an annual production of 37 million tons and Ethiopia is the major durum wheat producer in Sub-Saharan Africa (SSA). Crop breeders have worked to create genotypes with improved grain production, quality, and other desirable qualities under a variety of diverse environmental situations. Genotype × environment (G×E) interaction is one of the main complications in the selection of broad adaptation in most breeding programs. Objective: The goal of the study was to assess genotype by environment interaction in multienvironment trials and identify stable and adaptive durum wheat varieties using AMMI and stability measures. Method: The experiment was conducted at Beati-Maymesanu in Ganta-Afeshum Woreda, Agarba in Degua Tembein Woreda, Atsela in Emba Alajie Woreda, and Zata in Ofla Woreda during in 2015 and 2016 under Production and contrasting growing conditions. Thirty six durum wheat varieties were released using Simple Alpha Lattice design with two replications. This study was used AMMI and stability measures for assessing among environments and genotypes. Result: The Combined analysis of variance revealed highly significant difference among genotypes, environments and GEI for durum wheat. Stability analysis of grain yield was executed using environmental variance, shukla‟s stability, Wricks‟ ecovalence and AMMI stability value (ASV). The analysis of variance for the AMMI model were highly significant variation differences between genotypes, environments and the interaction effect of G x E. The first two interaction principal component axes (IPCA) of the AMMI model accounted for 48.73% of the total G x E interaction sum of squares for grain yield. Conclusion and Recommendation: According to the AMMI biplot analysis, Genotypes G30 (55D3), G11 (248478) and G25 (236295) were more stable, while, G33 (222415) and G21 (8436) are the unstable genotypes and E5 (Beati-Maymesanu-2016) was the highest yielding environment while, E8 (Zata-2016) was the low yielding among eight environments. Keywords: AMMI, Genotype by Environment interaction
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    Prevalence & Risk factors of Patent Ductus Arteriosus (PDA) in Preterm Neonates: Evidence from Survival & Shared Frailty Model
    (Mekelle University, 2023-11-28) Nigus Gebreab
    Background: The ductus arteriosus is a leftover fetal artery connecting the main body artery (aorta) and the main lung artery (pulmonary artery). The ductus allows blood to detour away from the lungs before birth. Every baby is born with a ductus arteriosus. After birth, the opening is no longer needed and it usually narrows and closes within the first few days. Patent ductus arteriosus (PDA), resulted when this artery remains open (patent) after birth, is a heart problem that occurs soon after birth in some babies. Its human and economic loss is too much in general if it is not treated at all or treated early. Objective: The overall objective of this study was to assess prevalence of PDA in preterm neonates; their survival time (time to death) & associate risk factors. Methods: To address the study objective, a secondary data from Health Facilities of Mekelle City was collected from 125 preterm neonates who initiated their follow up between December 2019 and December 2020. The Cox PH model with parametric shared frailty distribution where hospitals (health facilities) preterm neonates treated used as a clustering effect in the models. The gamma and inverse Gaussian shared frailty distributions with Exponential, Weibull and log-logistic baseline models was employed to analyze risk factors associated with age at circumcision using socio-economic and demographic factors. All the fitted models were compared by using AIC and BIC values from actual dataset. Results: A total of 125 children were seen at the Health Facilities of Mekelle City during the study period. The result revealed that about 20% of preterm neonates were exposed to PDA while the remaining were not. The AIC value for the three baseline distributions (Exponential, Weibull, and Gompertz) of PH model was found 173.6275, 174.6895, and 175.6086 and the BIC value of those baseline distributions for the same model was also found 216.0522, 219.9425, and 220.8616 respectively. The AIC value for the three baseline distributions for gamma shared frailty model was found 172.5497, 176.6895, and 176.6896 (the same value with Weibull) and BIC value of those baseline distributions for the same model also found 220.8805, 224.7708, and 224.7708 (the same with Weibull) respectively. Based on AIC and BIC values from simulation experiment and graphical evidences, Gamma shared frailty model, with the exponential baseline preferred when compared with other models. The clustering effect (the hospital effect) was significant for modeling the determinants of time-to-death preterm neonates with PDA. The estimated value of ix | P a g e theta (θ) which is a measure of contribution of a frailty component to the model was 1.1056 and a chi-square value of 0.003722 with one degree of freedom resulted a p-value of 0.0027. Based on the result of Gamma shared frailty model with the exponential baseline, gestational age, birth weight, place of delivery at home, maternal history with HIV, and treatment with paracetamol were found to be the most significant risk factors of the outcome variable, survival time (time to death from PDA). The hazard ratio and 95% Confidence interval of gestational age and birth weight was also 2.0742 with CI (0.5905259, 0.9013781) and 2.7191 with CI (1.000007, 1.000614) that yielded a p-value of 0.003 and 0.045 respectively. The hazard ratio and 95% CI for the covariates place of delivery at home, maternal history with HIV, and treatment with paracetamol were 5.1852 with CI (0.7416363, 5.1268725), 2.139 and (2.417719, 263.6325), and 42.0056 with (-3881.608, 3846.564) which yielded a p-value of 0.0092, and 0.007 respectively. They have also a prevalence rate of a unit (for place of delivery at home and maternal history with HIV) and 0.13 for treatment with paracetamol (No). The overall prevalence rate was also yielded 0.32. Conclusions: The model suggested that there is a strong evidence of heterogeneity among health facilities where the preterm neonates were treated. From the candidate models, Gamma shared frailty model, with the exponential baseline was an appropriate model for predicting the PDA data. There was a frailty effect on the survival of the preterm neonates that arises due to differences in the distribution of hospitals of the neonates. The risk factors place of delivery at home, maternal history with HIV, gestational age (week), Birth weight, and treatment with paracetamol were statistically significant for the survival of preterm neonates whereas the other risk factors were not statistically significant. The frailty component had also a significant effect to the model
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    Bayesian Survival Analysis of Adult Tuberculosis Patients: the Case of Lemlem Karl Hospital, Maichew, Southern Tigray.
    (Mekelle University, 2024-11-28) Lemlem Tekle
    Tuberculosis is an airborne disease caused by the bacterium Mycobacterium tuberculosis, primarily affects the lungs. Transmission occurs through the air when individuals with pulmonary TB are not undergoing proper treatment. This study aimed to identify factors affecting the survival time of adult TB patients in LKH, Maichew, and Southern Tigray. To address the objective of this study, 242 adult TB patients were included in the study based on data taken from the medical records of patients enrolled from July; 2020 to January; 2024. Almost half, 50.4%, of the adult TB patients were female. Kaplan Meier plots were used for comparison of survival function; Bayesian survival models were used to identify factors affecting the survival time of adult TB patients. Of the total patients in the study 178 (73.6%) were censored. The estimated median survival time of patients was 26 months. Bayesian log-normal accelerated failure time model using MCMC and INLA method fit adult TB data better than other Bayesian accelerated failure time models used in this study. The Bayesian log-normal accelerated failure time model using the INLA method was preferable to the MCMC method due to smaller standard error and narrow credible interval. The results of this model show that the survival time of adult TB patients is significantly affected by age, residence, body weight, HIV status, BMI, dose level and cigarette smoking of adult TB patients(pvalue<0.05). Bayesian log-normal accelerated failure time model using the INLA method describes the adult TB dataset well. From the Bayesian result, the risk factors for the survival time of adult TB patients were age group (31 to 45, 𝛾 = 0.8607),(46 to 60, 𝛾 = 0.7189)and( >60, 𝛾 = 0.6637);residence(rural,𝛾 =0.7408); HIV (Positives, 𝛾 = 0.68386); Dose (III, 𝛾 = 0.6570) ,IV 𝛾 = 0.9512),BMI(Overweight, 𝛾 = 0.8607) and (Obese 𝛾 = 0.0779); base line weight(> 50kg, 𝛾 = 0.8693) and (smokers, 𝛾 = 0.8607) at 95% credible interval and those factors were prolonged the timing death of adult TB patients. Therefore, health professionals should focus on the identified factors to improve the survival time of TB patients.
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    Analysis on utilization of maternal health care service in Ethiopia: Using Ethiopian Mini Demographic and Health survey
    (Mekelle University, 2023-11-28) Hiwot Amaha
    Background: The World Health Organization (WHO) established the "Safe motherhood package" as a manual for interventions in maternal and child health, and it lists antenatal care as the fundamental intervention in lowering maternal and infant mortality. Antenatal Care for women and children starts with their immediate health issues and extends to their long-term wellbeing as well as the wellbeing of the community. Getting in touch with mothers and identifying and managing present and future risks and issues are the main goals of prenatal care. It is regarded as one of the most crucial for the mother's health, the fetus's optimal development, and preventing or lessening pregnancy complications (Fantahun M, 1992). Methodology: This research used cross sectional study design retrieved from Ethiopian MiniDemographic and Health Survey 2019 to assess factors affecting utilization of maternal health care services in Ethiopia. This study analyzes responses from 3979 women age 15-49, who have at least one child under age five at the time the survey was fielded. Result: Women from Urban areas were more likely to receive ANC care than women from other rural areas. The bivariate results show a significant difference in the use of maternal health care services by age, marital status, women’s education, parity, wealth, religion, and family size as significant and independent predictors for the use of antenatal care. And age, wealth, region, residence, women’s education, parity, religion and family size are significance and independent predictors for the use of delivery care services in Ethiopia. Bivariant and multivariate analysis showed significant association between ANC and maternal age, women’s education, religion and wealth. Age (OR=1.527, 95%CI=1.102,2.116), Education (OR=1.731,95%CI=1.434,2.090), religion (OR=1.829,95% CI=1.386, 2.414), wealth (OR=2.234,95% CI= (1.758, 2.839) and residence (OR=.387,95% CI= 290, .516) were associated with choice of delivery site. Education and parity were found to be strong predictor of both antenatal care and delivery care. Conclusion: In brief, the study discovered low maternal health care utilization in the area. Increasing maternal health service coverage and promotion of IEC in the community are recommended.
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    A Mixed Effect Model for Unbalanced Longitudinal Haematocrit Level Evolution Progress of Chronic Kidney Failure Patients
    (Mekelle University, 2023-11-28) Getachew Beyene
    Background: Chronic Kidney Disease (CKD) or renal failure is a public global health problem with an estimated prevalence of as 8 to 16% worldwide. This study was conducted inorder to investigate the evolution of hematocrit levels over time in renal patients after their transplant and to determine how the evolution depends on the age and gender of the patient and other factors. Objective: The main objective of this study is to employ a mixed effect model to examine the unbalanced longitudinal evolution progress of hematocrit levels in chronic kidney failure patients. Methodology: This is a longitudinal study that consisted of 1160 patients who received a renal transplant. These patients were followed up for a period of 10 years at most. Haematocrit level was considered as the response while the covariates were time in years, gender and age of the patients just to mention a few. Different statistical methods such as explanatory analysis, multivariate regression model, two stage analysis and linear mixed effects model were employed to explore the evolution of hematocrit over time. Results: Results revealed that haematocrit levels in kidney transplantpatients evolve over time. Gender and age of the patient have significant effect on the evolution of haemotocrit levels. Males tend to have a higher increase in haematocrit levels over time than females. With regard to age, haematocrit levels tend to increase with increasing age. Furthermore, it was observed that experience of cardio-vascular problems before transplant and rejection symptoms did not have a significant effect on the evolutionof haematocrit levels. Conclusions: Hematocrit levels evolve over time and this evolution follows a quartic time effect. The change in haematocrit levels varies according to the gender and age of the patient after a kidney transplant. Patients starting with low haematocrit levels tend to have a larger increase overtime.
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    Shared Frailty Model in Survival Analysis of Time to Discharge Dynamics for Myocardial Infarction Adult Patients at Ayder Comprehensive Specialized Referral Hospital (Jan 1, 2018 - Dec 31, 2020)
    (Mekelle University, 2024-11-28) Gebrewahd Tewelemedhin
    Background: MI, commonly known as heart attack, happens when a blood clot obstructs the coronary arteries, resulting in decreased oxygen and nutrient supply to the heart muscle. MI continues to be a significant cause of morbidity and mortality globally, with variations in the time-to-discharge dynamics among patients. Understanding the time to discharge is crucial for optimizing patient care and resource allocation, particularly in settings with limited healthcare resources like Ayder Comprehensive Specialized Referral Hospital. Objective: The overall objective of this study was to investigate and gain a comprehensive understanding of the time to discharge dynamics in MI patients at Ayder Comprehensive Specialized Referral Hospital, using a survival analysis with a shared frailty model. Methods: To fulfill the study goal, secondary data from Ayder Comprehensive Specialized Referral Hospital was collected from 206 MI patients who initiated their follow-up between January 2018 and December 2020. K-M curves used to compare the survival curve for categorical variables and the univariable analysed used Cox regression model to select variable which were included in the multivariable analysis. The Cox PH model with a parametric shared frailty distribution was utilized, with the follow-up site where treatment was administered serving as a clustering effect in the models. The study employed gamma and inverse Gaussian shared frailty distributions alongside Exponential, Weibull, and log-logistic baseline models to analyze the risk factors associated with survival time until discharge, considering socioeconomic and demographic factors. All fitted models were compared using the AIC and BIC values derived from the actual dataset. Results: Of the 206 patients were seen at Ayder Comprehensive Specialized Referral Hospital during the study period. The results revealed that approximately 54% experienced the event, while 46% did not experience it by the end of the follow-up period. The AIC values for the three baseline distributions (Exponential, Weibull, and Gompertz) of the PH model were found to be 370.8967, 90.3539, and 96.2921, respectively. The corresponding BIC values for those baseline distributions were 424.1427, 146.9278, and 152.8661, respectively. The AIC values for the three baseline distributions for the Gamma shared frailty model were found to be 375.4022, 89.2839, and 98.5131, with the BIC values for the same model found to be 431.9761, 148.9278, and ix | P a g e By: G/wahd T. 155.4568, respectively. Based on the AIC and BIC values from the simulation experiment and graphical evidence, the Gamma shared frailty model with the Weibull baseline was preferred when compared to other models. The clustering effect (follow-up site) was found to be significant for modeling the risk factors of time-to-discharge patients with MI. The estimated value of theta (θ), which measures the contribution of a frailty component to the model, was 1.1056. A chi-square value of 0.00372 with one degree of freedom resulted in a p-value of 0.0031. Based on the results of the Gamma shared frailty model with the Weibull baseline, the follow-up site at the medical ward, obesity (BMI > 30), age (in years), weight, diabetes mellitus, family history of MI, uncontrolled blood pressure, high cholesterol levels, and male gender were identified as the most significant risk factors for the outcome variable, survival time to discharge. The hazard ratio and 95% confidence interval for patient age and weight were 0.9844 (CI [1.0105, 1.5116]) and 1.0101 (CI [0.0193, 0.9879]) with p-values of 0.002 and 0.019, respectively. The covariates, including follow-up site at the Medical ward, BMI with obesity (BMI>30), diabetes mellitus, family history of MI, uncontrolled blood pressure, high cholesterol levels, and male gender, exhibited hazard ratios of 2.4868 (CI [0.4281, 1.4369]), 2.3445 (CI [0.3901, 2.1253]), 2.7563 (CI [0.582, 1.5858]), 3.7139 (CI [0.0152, 1.3031]), 1.0726 (CI [0.3823, 1.8024]), 1.7318 (CI [0.3385, 1.3835]), and 4.1012 (CI [0.0110, 1.1967]), respectively, with associated p-values of 0.018, 0.001, 0.003, 0.021, 0.026, 0.013, and 0.001, indicating their respective impacts on the study outcomes. Conclusions & Recommendation: The model suggested that there is a strong evidence of heterogeneity among follow up sites where the MI patients were treated. From the candidate models, Weibull-gamma shared frailty model was an appropriate model for the MI dataset. There was a frailty effect on the survival of the MI patients that arises due to differences in the distribution of follow up sites. The risk factors follow-up site at the medical ward, being obese, age(in years), weight, diabetes mellitus, family history of MI, uncontrolled blood pressure, high cholesterol levels, and male gender were statistically significant for the survival of MI patients whereas the other risk factors were not statistically significant. Health care providers must focus on high-risk MI patients, considering factors like age, obesity, uncontrolled blood pressure, diabetes, high cholesterol level, gender, and family history of MI.
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    Modeling a Repeatedly Measured Farmyard Manure and Gypsum Intervention on Yield of Sorghum in Saline Sodic Soils
    (Mekelle University, 2023-11-28) Elias Tafere
    Background: Salinity is one of the major environmental problems the world is currently dealing with, and it also poses the biggest obstacle to agricultural productivity, especially in arid, semiarid, and dry sub humid regions. Sorghum is the most produced grain in Raya Alamata, Southern Tigray of Ethiopia. Soil salinity in this area often affects sorghum yield and yield characteristics. In order to tackle the effect soil salinity/sodicity status, ongoing assessment and monitoring on fertilizer intervention should be conducted in the stated study area Objective: The aim of this thesis is, hence, twofold: to propose repeated measure analysis to take into account the problems with traditional approach; and make use of this approach to scrutinize the optimum rate of gypsum and farmyard manure fertilizers for improving sorghum yield in saline sodic soils of Raya Alamata, Southern Tigray of Ethiopia with an emphasis on the use of mixed modeling techniques with repeated measures. Method: The study involved secondary repeated measure or longitudinal data, collected using field experiments during three consecutive years of the same plots to illustrate different modeling strategies and graphical tools with an emphasis on the use of mixed modeling techniques with repeated measures. Mixed modeling approach is the most flexible method in terms of handling the covariance among repeated measures. Result: The Breusch Pagan method shows Pooled OLS model is not the best estimation method (p-value=0.000). Hausman Test output also indicates random effect model outperforms compared to the fixed effect (p-value=1.000). The spaghetti plot showed that the increasing trend with time. A positive linear relationship was also observed between yield measurements taken at different years, confirming the strong correlation. The mean yield with 0% GR was 34.23qt/ha but 36.33 qt/ha and 37.58 qt/ha after addition of Gypsum 50%GR and 100% GR respectively. Similarly there was a better yield after adding FYM when compare to the control. The mean yield is increasing over time, the mean yield is 35.47, 35.94 and 36.72 at first, second and third year respectively. The maximum yield 40.25 also recorded in the third year. Sole application of 8 tha-1 FYM and combination of FYM and Gypsum rate at (50%GR+8 tha-1 FYM) have significance role on production yield of sorghum on salinity area of Raya Alamata over three consecutive years with p-value < 0.000 at =5% level of significance respectively. Conclusion and Recommendation: The study found that repeated measure analysis using mixed modeling techniques yields a better result than a traditional approach (OLS). The result from the Bonferroni mean comparison further revealed that combination 8tha-1 FYM and 50% GR are the optimum level of fertilizers that provide improved sorghum yield in saline sodic soils of Raya Alamata, Southern Tigray of Ethiopia.