arezoo bagheri

Divorce as an important social harm has always been the focus of investigators and policymakers as it affects women compared to males. Therefore, considering the importance and prominent role of women in the family and society, the present article aimed to examine the most important determinants of the first marriage survival of divorced women with children.

In a cross-sectional survey conducted by the Civil Registry Organization in 2017-2018, the information of those who referred to the offices of the provincial centers for divorce registration was collected using a questionnaire. Considering the large number of predictors and the ineffectiveness of classic survival analysis methods in big data modeling, the present study investigated the most important factors, including women and their spouses, their families and provincial macro variables, affecting the first marriage survival of 756 women with children using survival forests using R software.

Based on the highest value of Harrell's coordination index (0.8412), the lowest mean prediction error (0.0885) and the lowest value of integrated Brier score (0.038), the algorithm of random survival forest with log rank split rule (RSF1) in investigating factors affecting the first marriage survival of these women was more efficient. The findings showed that based on variable importance and minimum depth indicators, the first child’s age was the most important variable in examining their first marriage survival.

Since big data are analyzed in many medical and social studies, survival forests can be used as an efficient method to identify the most important predictors and reduce their dimensions, and then use classical survival analysis methods for modeling.

The Corona virus in the world has forced millions of people to quarantine at home and caused anxiety. The main objective of this study was to study the effect of socio - economic covariates by controlling demographic and health covariates on corona anxiety in Naghadeh. Using Proportional stratified multi-stage sampling 384 women and men over 20 years old were selected and a 24-item CPDI questionnaire was completed for them in the fall of 2019. Then, data were analyzed by Structural Equation Modeling in Amos Software. Accoridng to the results, Corona anxiety was more for Turkish people than Kurdish ones, for families with low and medium monthly expenses than those with high ones, and for people with low and medium assessments of the future situation than thoes with high ones. People whose family members were not infected with Corona, used Internet and believed that Corona had little effect on their family compared to those whose one of their family members were infected with Corona, didn’t use internet, and emphasized family disputes had less anxiety. Also, by increasing economic insecurity feeling, the Corona anxiety increased.

It seems necessary to identify underlying factors of conflict between couples, and especially women before starting marriage life, to prevent divorce in the later stages of marriage. The current study aims to investigate the factors affecting First Marriage Survival (FMS) of 279 divorced women without marriage life experience. First, the most important determinants of women’s FMS were selected using the non-parametric survival forest approach, and then parametric survival models were fitted to the data. FMS of 17.9% and 30.1% women were less than one year and 1-2 years, respectively. Using the most efficient survival forest algorithm in forecasting, important covariates were extracted and the shared frailty Weibull accelerated failure time model was fitted as the final FMS model; educational years (P-value=0.001) and informal (P-value=0.013) and formal (P-value=0.007) acquaintance years had significant effects on these women’s FMS. Therefore, it is necessary to adopt appropriate policies to provide the possibility of employment for educated women, increase the formal acquaintance duration, and reduce the informal acquaintance duration to survive women's marriages in the pre-marriage period.

Work hope, as one of the dimensions of social hope, can lead to the promotion of economic and social resilience in society. In order to investigate this index, the present article studies the demographic and socio-economic factors affecting work hope in Tehran. Data of 1200 respondents were collected through a questionnaire and multi-stage stratified sampling in 2017 and analyzed applying GSEM. Findings showed that women comparing to men, the unemployed compared to the employed and residents of less-developed and middle-developed areas comparing to developed and more developed areas had less work hope. By increasing age and psychological insecurity feeling, work hope decreases and by increasing number of educational years and organizational trust, work hope increases. the significant indirect effects of the number of children, the number of hours using Internet and the socio-economic insecurity feeling showed that increasing these variables reduces the work hope. The results also showed that failure to meet the job expectations of respondents, especially women, the unemployed, residents of less developed area and the elderly leads to polarization of society and formation of class divisions. The policy message of the present study is that in order to spread work hope among the citizens of Tehran, the positive impact of educational level and organizational trust variables, especially among residents of developed area should be used as a valuable opportunity.

Today, universities compete with each other in several areas, including the dimensions of student management at the national and international levels. This study intends to review and design a strategic model for the development of entrepreneurial competencies of students of the University of Applied Sciences. The main purpose of this study is to design a strategic model for the development of entrepreneurial competencies of students of the University of Applied Sciences. Due to the nature and objectives of the research, in order to answer the research questions, theorize and provide a background model for the development of entrepreneurial competencies, the data theory theory method of the foundation is on the agenda. Using the foundation data theory method can achieve the goal of developing applied knowledge in the field of entrepreneurial competencies to assist in future decisions. The statistical population of the present study includes senior managers, middle managers, experts in charge of Guilan University of Applied Sciences, which according to the report of Guilan University of Applied Sciences were 20 people. In this research, the data analysis process has been done during three coding stages due to its importance in the underlying theory approach. In the present study, with emphasis on organizational capabilities approach, students' entrepreneurial competencies in three main categories of passion strategy, ability strategy and orientation strategy and seven sub-categories including relationship with industry, private sector, financial sector, infrastructure, market structure , Organization and policies of the Ministry of Science were formulated.

The main purpose of this research was to design a strategic model for the development of entrepreneurship competencies of students of the University of Applied Sciences.

The present study was applied in terms of the purpose and qualitative in terms of the research method employed. The research population included the academic experts of Gilan University of Applied Sciences in the academic year of 2020-21, 17 of whom were selected based on the theoretical saturation method and purposefully. The research tool was a semi-structured interview, which was used to validate the findings from the re-review strategy by the researcher and formal validity (university professors) and for reliability, the coding agreement coefficient of two coders was used, which was 0.89. For data analysis, coding using thematic analysis method was used in MAXQDA19 software.

The findings showed that 115 initial themes, 12 central themes and 3 optional themes were identified for the strategic model of developing students' entrepreneurial competencies; So that the chosen themes included passion strategy (venture capital, innovation and high growth), ability (competition, technology absorption, human capital and new opportunities) and orientation strategy (opportunity understanding, risk-taking, cultural support, networking and skill).

According to the results, it can be said that the planners of the university system, on the one hand, should motivate and encourage and remove financial and structural obstacles to increase and develop the entrepreneurial skills of students, and on the other hand, they should focus on empowering entrepreneurs and the cultural and social contexts of entrepreneurship

 Total fertility rate (TFR) in Iran decreased from the year 2000 and recently Iran has experienced fertility rates below replacement level. Birth interval is one of the most important determinants of fertility levels and plays a vital role in population growth rate. Due to the importance of this subject, the aim of this study was analyzing three birth intervals using three Survival Recurrent Event (SRE) models.   In a 2017 cross-sectional fertility survey in Tehran, 610 married women, age 15-49 years, were selected by multi-stage stratified random sampling and interviewed using a structured questionnaire. The effects of selected covariates on first, second and third birth intervals were fitted to the data using the Prentice-Williams- Peterson-Gap Time (PWP-GT) SRE model in SAS 9.4.   Calendar-period had a significant effect on all three birth intervals (p <0.01). The Hazard Rate (HR) for a short birth interval for women in the most recent calendar-period (2007-2017) was lower than for the other calendarperiods. Women’s migration influenced second (P=0.044) and third birth intervals (P=0.031). The HR for both birth intervals in migrant women was 1.298 and 1.404 times shorter, respectively than non-migrant women. Women’s employment (P=0.008) and place of residence (p <0.05) also had significant effects on second birth interval; employed women and those living in developed, completely-developed and semi-developed areas, compared to unemployed women and those living in developing regions, had longer second birth intervals. Older age at marriage age increased the HR for a short third birth interval (p <0.01).    The analysis of birth interval patterns using an appropriate statistical method provides important information for health policymakers. Based on the results of this study, younger women delayed their childbearing more than older women. Migrant women, unemployed women and women who live in developing regions gave birth to their second child sooner than non-migrant employed women, and women who lived in more developed regions. The implementation of policies which change the economic and social conditions of families could prevent increasing birth intervals and influence the fertility rate.

Since determination of factors influencieng childbearing delay can provide convenient approaches to prevent fertility decline, nowadays studying this issue is an important issue for demographers and it is also emphasized by planners and politicians. The aim of this study is to evaluate factors influencing first birth interval among 458, young Iranian married women in Tehran province. In this cross sectional study, stratified random sampling was used to collect data of a structured questioner in 2017. Women’s first birth interval was compared in confronting some demographic, socioeconomic and attitudinal factors by Kaplan-Meier estimates and Log-Rank test as non-parametric survival analysis tools. The mean of women’s first birth interval was 3.33±2.67 years with a median of 3.00 years. Kaplan-Meier estimates were significantly different between levels of women’s and their husband’s educational level, activity, and post materialism factor (p-value<0.05). Women with university education and who had husbands with university educational level had the largest first birth interval among all other educational levels. Employed women had longer first birth interval than unemployed ones. Women lived with employed husband had shorter first birth interval. High post materialism women had the largest first birth interval.

During the last decades, the average gap between attitudinal and behavioral youths’ marriage age has increased due to the changes in Iranian society and family patterns. This paper is devoted to studying this increment.

Classification and Regression Trees (CART) are applied for modeling the marriage age gap (MAG) of 12741 youths selected by a multi-stage cluster sampling method from 31 provinces in Iran.

Classification accuracies of fitted CART for females’ and males’ MAG were equal to .62 and .60, respectively. The most influential variables on females' and males' MAG were educational level and the number of siblings, respectively. Females with "university education," "diploma and less education with 5 and more siblings", and “employed diploma and less education with 3 or 4 siblings" married later than their desired time. Males with "3 and more siblings", "employed with 2 and fewer siblings and 3 and more ideal number of children", "employed university educated with 2 and fewer siblings and 1 or 2 ideal number of children", and " employed with 2 and fewer siblings and 1 or 2 ideal number of children with a diploma and less education and negative opinion towards childbearing" also married later than their desired time.

If the inevitable experience of modernity doesn’t combine with the convenient policy and the economic and socio-cultural conditions of the community don’t change, the negative consequences of such developments would be more than its positive achievements on different social issues especially and more importantly youth’s marriage age.

Fertility is one of the important subjects in public health and demographic studies which affects population growth. The main objective of this paper was to introduce and apply a tree model to classify the ideal number of children and children ever born in the study of "Marriage and Fertility Attitudes of Married 15-49 Years Old Women in Semnan Province in Iran, 2012".

Classification trees are data mining methods designed for categorical dependent variables, with prediction error measured in terms of misclassification cost to determine the form of the relationship between the response and predictor variables in different field of studies.

We applied the Classification and Regression Trees (CART) algorithm to present the merits of this algorithm to accurately classify the ideal number of children and children ever born of 405, 15-49-year-old married women in Semnan providence, Iran, according to some important predictor variables. Semnan is a province that is taking efficient steps toward development and modernization. Nowadays, it is considered as one of the developed provinces in Iran. In this province, changes in fertility attitudes and beliefs expected to be affected by modernization, industrialization, and urbanization.

As a result, the women’s children ever born in the younger birth cohorts and the ideal number of children in the older birth cohorts are much more similar. Women’s job status and age at first marriage are the two most important factors which have had significant effects on the desired and actual number of children in different birth cohorts.

According to health surveys, population growth and total fertility rate (TFR) are decreasing in Iran. The economic and social factors in addition to the changing values and attitudes in the Iranian society have had a major impact on fertility decisions and the actions of families, especially women towards childbearing. This is an important issue for policymakers and many researchers in demography and public health thus the investigation of factors that affect low TFR is considered as a necessity.

The classification and regression trees (CART) algorithm, as one of the most applicable classification trees, along with logistic regression was applied to model the tendency of 4898 women for childbearing in provinces with a TFR lower than the replacement level in Iran. The secondary data were then analysed by SPSS version 24.0.

Based on these two approaches, it was concluded that despite the CART algorithm, logistic regression suffers from some shortcomings including the difficult interpretation of three levels of interactions while not containing a specific method for handling the outliers. In addition, CART results demonstrated that women’s children ever born (CEB), age, and opinion had significant impacts on their desire to have a child. The groups encompassing “10-39-year-old women with CEB≤2” and “40-49-year-old women with positive attitudes towards childbearing” desired to have more children while “women with CEB ≥3” showed no tendency for childbearing.

In general, the results revealed that adopting policies for changing women’s views on childbearing and creating the necessary resources for preventing the delays in marriage are regarded as important actions toward altering fertility rates. Another important conclusion is applying the CART algorithm as a convenient method for classifying demographical data.

Application of statistical machine learning methods such as ensemble based approaches in survival analysis has been received considerable interest over the past decades in time-to-event data sets. One of these practical methods is survival forests which have been developed in a variety of contexts due to their high precision, non-parametric and non-linear nature. This article aims to evaluate the performance of survival forests by comparing them with Cox-proportional hazards (CPH) model in studying first birth interval (FBI).

A cross sectional study in 2017 was conducted by the stratified random sampling and a structured questionnaire to gather the information of 610, 15-49-year-old married women in Tehran. Considering some influential covariates on FBI, random survival forest (RSF) and conditional inference forest (CIF) were constructed by bootstrap sampling method (1000 trees) using R-language packages. Then, the best model is used to identify important predictors of FBI by variable importance (VIMP) and minimal depth measures.

According to prediction accuracy results by out-of-bag (OOB) C-index and integrated Brier score (IBS), RSF outperforms CPH and CIF in analyzing FBI (C-index of 0.754 for RSF vs 0.688 for CIF and 0.524 for CPH and IBS of 0.076 for RSF vs 0.086 for CIF and 0.107 for CPH). Woman’s age was the most important predictor on FBI.

Applying suitable method in analyzing FBI assures the results which be used for making policies to overcome decrement in total fertility rate.

Socio-economic factors, in addition to value and attitude changes, have had a major impact on fertility behavior of women toward childbearing. The main purpose of this study is to investigate childbearing desire of 6183 women in provinces with total fertility rate (TFR) lower (TFR ≤ 2) and upper (TFR > 2) than replacement level by classification and regression trees (CART) algorithm, as one of the most applicable classification trees. In this study women’s job, place of residence, age, opinion, marriage age, educational level, and children ever born were investigated as predictors. The accuracy of fitted classification trees for CD in provinces with TFR ≤ 2 and TFR > 2 were 0.68 and 0.72, respectively. As a result, women’s children ever born and age had significant roles on their desire to have a child in all provinces while their opinion toward childbearing had just effect on provinces with TFR ≤ 2. In provinces with TFR ≤ 2, 10 - 39 years old women with 2 children and less CEB were willing to have another child. Women with 2 or less children at the age of 10 - 29 as well as women with 3 or more than 3 children at the age of 20 - 29 had a desire for more children in provinces with TFR > 2. If the women have a positive attitude toward childbearing and their age is not high, they will desire to give birth to a child until they reach the ideal number of their children. Thus, policies in changing their attitudes toward childbearing and creating the necessary facilities to prevent delays in marriage could be an important step in changing fertility rates.

Demands for more children have substantial effects on couple’s fertility behaviors. The ideal number of children for most Iranian’s family is two, so that it is reasonable to study which factors determine women’s decision to have a third child. The main aim of this study was to examine factors affecting the demand for a third child (DTC). This cross-sectional study was conducted on 6231 Iranian married women from all provinces during autumn 2014. Participants in the study were selected by multistage stratified sampling method. A structured questionnaire was employed to collect the related data. Finally, the analysis included 2272 DTC questionnaires for women with two children by applying a classification tree model. In this study,50.7% of women with two children had no desire for having the third child, out of whom 71.1% (79) were living in the provinces with total fertility rate (TFR) less than 2 and in urban areas, respectively. Most of them with the educational level of diploma or lower (78.2%) had a negative opinion about having the third child (36.1%). Based on the classification and regression tree algorithm, women who were interested in having their third child in provinces with TFR more than 2 included rural women, urban women with positive opinion toward childbearing, and those with educational level of secondary school. However, women who were keen on having their third child in provinces with TFR less than 2 consisted of urban women aged 30-49 with educational level of high school or lower, those younger than 30 years with positive opinion who married in their 20-29, rural women aged less than 30, and rural women aged 30-49 with positive opinion who married in their 20-39. Women’s place of residence and opinion toward childbearing had important effects on their DTC. However, women’s educational level as well as their age and marriage age could affect their DTC in provinces with TFR less than 2 compared to other provinces.

A set of economic and social rules and regulations as well as cultural factors influence value of children; however, this value itself could alter fertility behaviors. The present study aimed at investigating the influence of the value of children on fertility behavior through considering the impact of its attitudinal factors on childbearing desire, as one of the most important dimensions of fertility behavior. A cross-sectional study was conducted on 6231 females from 31 provinces of Iran, admitted to public health and treatment centers to vaccinate their children, during year 2014. The data collection tool was a questionnaire, including three value of children dimensions, including cultural (five items), social (seven items), and economic (four items) factors, and also demographic and attitudinal questions. Data were analyzed using SPSS-17 software and the factors influencing childbearing desire (CD) were examined by four SEMs for four age groups in AMOS-22. Goodness of fit models was confirmed by five fit indices. Only cultural factors had a significant direct effect on CD for 30 to 39 and 40 to 49 year-old females (P-values = 0.027, and < 0.001, respectively). Thus, planners and policy makers should consider changes in the cultural value of children to implement successful policies to alter the current decreasing trend of fertility rate.

One of the features of fertility below replacement level is the increase of the first birth interval which has occurred at the same time with the rise of women’s marriage age in recent years in Iran. Since determination of factors affecting delay in childbearing can provide convenient approaches to prevent fertility decline, the aim of this study was to evaluate socio-economic factors influencing the first birth interval in married women in Tehran province, Iran.
In a cross-sectional study, 610 married women aged 15 to 49 years were selected by the stratified random sampling and a structured questionnaire was used in 2017. Women’s first birth intervals were compared in terms of some demographic and socio-economic factors by Kaplan-Meier (KM) estimates and Log-Rank test for univariate and Cox model for multivariate survival analysis using SPSS version 22.0.
The mean of women’s first birth intervals was 3.181±0.101 years. Women’s educational level and social insecurity had significant effects on the first birth interval (P value According to results, unless governments provide the condition of social security, reducing the interval between marriage age and childbearing will not be attained.

Rapid social, economic and cultural changes along with intentionally or unintentionally consequences has provided the incidence and spread of social pathologies such as street children in large cities. Probability and non-probability sampling methods that are used to study this data are faced many problems such as coverage error and invalid statistical inferences, respectively.
Respondent driven sampling method is an effective method to penetrate the hidden and hard to reach layers of the target population. The main objective of this paper was to introduce this method, obtain unbiased proportion estimates, as well as evaluate effectiveness of this method in a study of street children in Tirana, Albania (2010).
According to the results of this survey, success of respondent driven sampling method for studying street children lies on knowing the exact size of social networks for these children, availability of survey sites, reaching to equilibrium in interested variables and selecting appropriate incentives.
Accomplishing accurate findings of street children without the presence of a representative sample would not be possible and it would not be achieved unless researchers use effective sampling methods to study these populations. Indeed driven sampling is recommended.

Despite the success of family planning programs in Iran in the recent decades, considerable proportions of pregnancies are still unintended and can be a cause of poor mental and physical health of the mother and child. The aim of this study was to investigate some important factors affecting uplanned pregnancies among married women in Semnan province, one of the developed provinces of Iran with below replacement fertility level.
The data for this study were drawn from a cross-sectional survey conducted in Semnan province in 2014. A total of 363 married women within the age range of 15-49 years who were pregnant or had the history of at least one delivery were considered. The study sample was selected using multi-stage stratified sampling method. The data were collected using a self-structured questionnaire with 90 items and Cronbach's alpha coefficient of 0.88. Data analysis was performed in SPSS (version 20) using Crammer’s V coefficients and Chi-square tests. Logistic regression analysis was also applied to model the risk of unintended pregnancies based on selected covariates.
According to the results, around 18.2% of the pregnancies were unplanned, 7.7% and 10.5% of which were mistimed and unwanted, respectively. Based on the logistic regression analysis, birth cohort, number of children ever born, and contraceptive methods had significant effects on the risk of unintended pregnancies. Furthermore, about 48% of the women experiencing unintended pregnancy were using a traditional contraceptive method before or at the time of the conception.
As the findings indicated, the women who used contraceptive method, as well as those with higher number of children and younger birth cohorts had higher risk of unplanned pregnancies. It should be noted that the majority of unplanned pregnancies among the women in younger birth cohort were mistimed pregnancies. So it is recommended to continue offering family planning and health services to these women in order to prevent unplanned pregnancy, unsafe abortion, and many chronic diseases.

Early and delayed marriage has their own effects on mothers and their children's health and social dimensions. Nowadays, Iran experiences delayed marriage due to several factors; thus, the present study was concocted to investigate the factors affecting youths’ marriage age, and to compare these factors between males and females.
To study demographic, socio-economical, and some atitudinal behavior factors affecting the age of marriage, in the current cross-sectional study, 12741 Iranian pre-married youths including 6381 males and 6360 females from all provinces were selected using multi-stage stratified method and the data was collected using a structured questionnaire in 2014. The questionnaire included demographic, socio-economical, and some atitudinal behavior questions about childbearing. Kaplan-Meier, Log-Rank test, and parametric survival analysis were applied in IBM SPSS Statistics for Windows, Version 22.0., and SAS 9.3 software.
Gamma and Log Logistic parametric models were the best fitted models for females’ and males’ marriage age, respectively. Females and males who lived in provinces with TFR Young females and males had the same factors influencing their marriage age.

Socio-economic factors, following psychological factors, affect the value of children in parents’ view and this value itself could influence Ideal Number of Children (INC), which is one of the most important dimensions of fertility behavior. The aim of the present study was to investigate parents’ INC according to the factors influencing the value of children from the viewpoint of men and women, separately.
In a cross-sectional study, multi-stage stratified sampling method was conducted to collect data from 590 males and 610 females in Tehran province, Iran, using a questionnaire including demographic and attitudinal questions. To describe data, SPSS-17, and to examine the factors influencing INC, path analysis was used in AMOS 22 and Goodness of fitted model was approved using the relative chi-square ( , Goodness of Fit Index (GFI), Adjusted GFI (AGFI), and Root Mean Square Error of Approximation (RMSEA) indices.
Indices of Goodness of fit confirmed the fitted models ( =2.289, GFI=0.994, AGFI=0.973, and RMSEA=0.047 for males’ model and =0.511, GFI=0.989, AGFI=0.994, and RMSEA=0.020 for females’ model). Negative psychological (males’ coefficient=-0.20 and females’ coefficient=-0.17, P According to the results of the present study, significant factors influencing INC of males and females were negative psychological and positive economic factors of the value of children and the negative social factor of value of children was the only significant factor influencing INC for males.

In many medical and epidemiological studies, each person can experience several events one after the other sequentially under some circumstances, known as recurrence events. Broad analytical objectives of recurrent events consist of describing event process in an individual, dispersion of events from one person to another, and determination of relations between constant or time-dependent predictors with event time. So the main purpose of this article is to present and interpret advanced statistical models to analyze such events which have been proposed in recent years.
In this article, variance-corrected models including AG, conditional PWP (PWP-TT and PWP-GT) and marginal WLW models for analyzing recurrent events are presented and compared with each other.
When the number of events for each individual are small and the risk of a reoccurrence of an event varies between different events, usually conditional PWP models are used, while marginal WLW and the time-dependent AG models are applied to determine frequency of events.
Medical and epidemiology studies should consider various factors such as the number of events, relationship between events, the variability of the effect of factors from one event to another, the biological process, and the correlation structure of data to select the valid recurrent models.

Considering the necessity and importance of the existence of water as a living resource, and at the same time, increasing population and the growing need for this source, providing water for drinking, agricultural and industrial purposes is one of the serious challenges in today’s world. The Karst can be a good source for water supply. The studies and researches of Karst water resources, due to limited alluvial resources in terms of quality and quantity and due to the wide expansion karst formations in the country, have particular importance. Khorin limestone is located in the northwest of Kermanshah city, where the main waters of the settlements around this area and the Hashilan lagoon are provided by the springs, Mirage and karst aquifers of this mountain. Therefore, in this study using the Fuzzy Logic / AHP model and employing eight effective criteria, the zoning map of potential Karst water resources of region was prepared. Then, to ensure the obtained areas, they were evaluated by field operations and geophysical methods. The results of the plot prepared with the fuzzy logic model showed that the southern ridge of Khorin and around the Hashilan lagoon had the capability and the potential of more Karst water resources. In order to validate this work, field operations and data collection was performed by vertical electrical sounding method in two separate profiles in the southern and northern slopes of the Khorin Mountain. The presence of a rich source of high quality water in the middle section of the southern slope and the lack of water resources in the northern slope confirmed the accuracy of the zoning results by the Fuzzy Logic / AHP model.

Around two decades ago, the Respondent Driven Sampling (RDS) method was introduced to sample hidden populations especially those exposed to high risk diseases. This study is aimed to determine factors affecting the design of sampling method for hidden populations exposed to high risk diseases.
In this review article, in addition to introducing the RDS method, 11 surveys that employed this method to study hidden populations are reviewed. Consequently, the key points that should be considered in designing this method including formative assessment and seeds selection are studied.
Results indicated that if the main purpose of a formative assessment and seeds selection does not achieve the hidden population parameter estimates will differ actual values and the survey would counter some biases. Uncertainty of recruiter’s degree, not-forming long recruitment chains, and slowly recruiting of recruiters could be the most important of these biases.
Without paying attention to the influential considerations in designing RDS method, this method in sampling hidden populations will not be applicable. It is recommended that researchers in order to guarantee the successful penetrating to the target hidden population, consider the key influential points RDS method in advance.

Many populations which are in the most focus of policy-makers are hidden or hard to reach populations that are formed by people with certain condition such as HIV infection. A careful study of these populations in order to their identification is very important, since their high risk behavior jeopardizes public health. Thus, defining a reliable and valid sampling method of them is also very vital. Applying conventional sampling methods (probability) to take samples from these populations since there is rarely a list or sampling frame of them are not practical and these methods are associated with coverage error. Non-probability sampling methods such as chain referral sampling also do not produce statistically valid estimates. One of the valid methods to take samples from these populations is respondent driven sampling method. In this sampling method, one of the most important sources of non-sampling errors is the bias which results from homophily. To check the validity of samples taken from this sampling method, in this article homophily is introduced which is a tool to assess the level of bias and the representative of samples. The main objective of this article is to examine the consequences of homophily in the production of unbiased estimators in this sampling method.

Since society health is endanger of high risk diseases, always populations exposing these diseases especially hidden populations are considered by researchers and policy makers in the field of public health. Conventional methods that are used by researchers for sampling and also computing estimation of population proportions, often lead to under or over estimations of these proportions in the interested populations. Despite the introduction of efficient sampling methods such as respondent driven sampling method for more than two decades ago, due to unfamiliarity of researchers in this field to the technique of calculating estimations for samples in this method, this sampling method is applied less for estimating proportions of hidden populations.
The main objective of current article is to identify estimators of population proportions for qualitative variables such as catching disease by the usage of estimating probability of inter- and cross-relationships, and social network size of respondents.
Findings: Existing theories and computer simulations have shown that estimators introduced for population proportions are asymptotically unbiased and have high rate of convergence.
Due to the lack of proper selection of sampling method and also computing method for estimating proportions of hidden populations, that generally exposing high risk diseases and are effective in health policies, acceptable results in achieving the objectives of this policy will not provide.