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    <title>DSpace Collection:</title>
    <link>http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/677</link>
    <description />
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        <rdf:li rdf:resource="http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/1072" />
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    <dc:date>2026-04-29T11:23:38Z</dc:date>
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  <item rdf:about="http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/1072">
    <title>Estimation of current population mean using two-occasion successive sampling with one auxiliary variable</title>
    <link>http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/1072</link>
    <description>Title: Estimation of current population mean using two-occasion successive sampling with one auxiliary variable
Authors: Zoramthanga, R
Abstract: In this study, two-occasion successive sampling for ratio-to-regression estimator was used to&#xD;
determine the current estimate of the population mean using only the matched part and one&#xD;
auxiliary variable, which is available on both the occasions. The data used were based on the&#xD;
total number of female workers in villages in Mizoram with the total number of literate female in villages in Mizoram as an auxiliary variables. The data were gotten from Census of&#xD;
India 2001 and 2011. The optimum mean square error of the combined ratio-to-regression&#xD;
and ratio estimator has been compared with (i) the optimum mean square error of the chaintype ratio estimator (ii) mean per unit estimator and (iii) combined estimator when no auxiliary information is used at any occasion. This result showed that the combined ratio-toregression and ratio estimator is more efficient than the other three existing estimators.</description>
    <dc:date>2018-04-12T00:00:00Z</dc:date>
  </item>
  <item rdf:about="http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/1070">
    <title>Temporal Dynamics of Malaria in Mizoram: A District wise Analysis</title>
    <link>http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/1070</link>
    <description>Title: Temporal Dynamics of Malaria in Mizoram: A District wise Analysis
Authors: Zoramthanga, R
Abstract: India is the largest contributor of incidence of malaria cases and related deaths in southeast Asian&#xD;
region. The state of Mizoram is one of the significant contributors of Malaria cases in India. The&#xD;
present study focuses on the transition of malaria cases in the districts of Mizoram from 2011 to&#xD;
2020. Various indicators including total malaria cases (TMC), Percent of P. falciparum (% Pf),&#xD;
Annual Parasite Index (API), Total positivity Rate (TPR), Annual Blood Examination Rate&#xD;
(ABER), and malarial deaths are processed through descriptive statistics, correlation and ANOVA&#xD;
to understand the disease epidemiology for Mizoram. Results revealed that Lawngtlai, Lunglei and&#xD;
Mamit districts are the top three in average number of malaria cases while Champhai recorded the&#xD;
lowest cases of malaria. Mamit recorded the highest number of malaria related deaths. Age group&#xD;
wise analysis showed that Malaria prevalence is highest in 15+ years of age, and the lowest is in&#xD;
0-4 years of age. The malarial incidences were highest in the year 2015 for different age groups&#xD;
and sex. Correlation analysis results in significant correlation between TMC vs API, TMC vs TPR,&#xD;
API vs TPR in district Lawngtlai. District wise analysis of Malaria cases showed statistically&#xD;
significant difference (p &lt;0.01) between Lawngtlai and Mamit, Lawngtlai and Saiha, Lawngtlai&#xD;
and Serchhip, Lawngtlai and Serchhip. Findings of this study help in policy interventions and&#xD;
framework. State Vector Borne Diseases Control Programme (Malaria) Mizoram should increase&#xD;
intensified surveillance and monitoring of malaria cases, targeted vector control interventions,&#xD;
improved access to malaria diagnosis and treatments, community-based education and awareness&#xD;
programs.</description>
    <dc:date>2024-08-27T00:00:00Z</dc:date>
  </item>
  <item rdf:about="http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/679">
    <title>Estimation of current population mean using two-occasion successive sampling with one auxiliary variable</title>
    <link>http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/679</link>
    <description>Title: Estimation of current population mean using two-occasion successive sampling with one auxiliary variable
Authors: Zoramthanga, R
Abstract: In this study, two-occasion successive sampling for ratio-to-regression estimator was used to&#xD;
determine the current estimate of the population mean using only the matched part and one&#xD;
auxiliary variable, which is available on both the occasions. The data used were based on the&#xD;
total number of female workers in villages in Mizoram with the total number of literate female&#xD;
in villages in Mizoram as an auxiliary variables. The data were gotten from Census of&#xD;
India 2001 and 2011. The optimum mean square error of the combined ratio-to-regression&#xD;
and ratio estimator has been compared with (i) the optimum mean square error of the chaintype&#xD;
ratio estimator (ii) mean per unit estimator and (iii) combined estimator when no auxiliary&#xD;
information is used at any occasion. This result showed that the combined ratio-toregression&#xD;
and ratio estimator is more efficient than the other three existing estimators.</description>
    <dc:date>2018-04-12T00:00:00Z</dc:date>
  </item>
  <item rdf:about="http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/678">
    <title>STATISTICAL ANALYSIS OF INFANT MORTALITY RATE IN MIZORAM.</title>
    <link>http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/678</link>
    <description>Title: STATISTICAL ANALYSIS OF INFANT MORTALITY RATE IN MIZORAM.
Authors: Zoramthanga, R
Abstract: Infant Mortality Rate (IMR) is the number of children who die before completing his or her first birthday day. It is usually taken as per 1000 live birth. According to census 2011, the population of Mizoram was 10.97 lakhs only and the study of Infant Death is very important for our future. Therefore, this paper is based on statistical analysis of infant mortality rate in Mizoram. In this paper, we use secondary data from “HEALTH AND FAMILY WELFARE DEPARTMENT” Government of Mizoram. In this paper, we apply time series trend for determine the trend and estimate the parameters. We also followed the trend to forecast for the next 10 years and the Quadratic Model is the best model to forecast. Based on our findings, we need more workshops or public awareness about maternal healthcare, so that we can alienate from Mizoram and we can make a better Mizoram for the future.</description>
    <dc:date>2022-12-18T00:00:00Z</dc:date>
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