# Post-Flood Risk Management and Resilience Building Practices: A Case Study
## 3 Research Methodology  
The mixed-method research approach incorporates the characteristics of quantitative and qualitative research to give aggregate results obtained from complicated research questions [26]. A mixed-method research design has been used for this study because it is descriptive as well as exploratory in nature. Descriptive research is applied to describe the major gaps in the flood response plans of the Government and other non-governmental humanitarian sectors during and post 2010 flood events in District Layyah and how did they play their role [22]. The exploratory dimension of research relates to gaining knowledge of flood risk management and explore how to embed the Disaster Risk Reduction, mitigation, and adaptation strategies at the local government and community development planning level. It also helps to investigate the structures if they are resilient against floods. A questionnaire survey technique has been employed and 200 samples were drawn from residents of the four most devastated Union Councils of Layyah District. The survey was conducted in 2013. The survey team comprised three members, including the researcher and two volunteers from a local NGO (IDSP). Each questionnaire respondent was the head of his/her family. The sample drawn from each Union Council was 50 each (randomly selected from the list of the residents within each union council and was ensured that the selected respondents were victims of the 2010 floods), as it is stated by [PERSON] and [PERSON] [27,28], that for each subgroup at least 20 to 50 sample size is sufficient for analysis. The major issue associated with the sample size is the selection of number (size) to perform the data analysis adequately and precisely. While using descriptive statistics (e.g., mean, frequencies), then nearly any sample size will serve well. Generally, a sample size of 200-500 is a good size sample when we need to perform multiple regressions, analysis of covariance, or log-linear analysis. This type of analysis is often applied to perform more rigorous state impact evaluations. Therefore, the selection of the sample size should be made appropriately for the planned analysis. Particularly, for the comparative analysis of subgroups (e.g., an evaluation of program participants with nonparticipants), an adjustment in the sample size might be required. It is clearly established by [PERSON] (1976), that a minimum of 100 samples is required for each major group or subgroup in the sample and for each minor subgroup sample size of 20 to 50 elements is obligatory ([PERSON] 1976, [PERSON] 1992). Based on this observation, we set the sample size of all small union councils to 50, which is sufficient for analysis by keeping in mind the targeted population. However, there are certain limitations of using a sample of the population for a questionnaire-based survey, such as (1) failure in the identification of the target population (2) consideration of inadequate survey population (3) the bias due to non-responses (4) bias due to respondents (5) questionnaire related problems in terms of content and wording, (6) questions should not be misleading, double-barreled, or ambiguous, rather they should be direct and clearly relevant to the survey objectives, (7) processing errors (8) misinterpretation of the results in relevance to the conducted survey (9) time period bias. Among the 200-sample size, there were 140 male respondents and 60 female respondents. The questionnaires for the community consisted of both open-ended and closed-ended questions to help in determining the socio-economic status of the local people, their concerns about the existing situation, their level of preparedness, and construction patterns of their structures while living in flood-prone areas. The first section of interview questions was related to the background information of the participants such as gender, age, locality, highest education level, family system, household size, number of bread earners, and occupation [24,25].