Citywide Mobility Survey (CMS) Household table contains data about the characteristics of the participant’s household, including household size, income, type of residence, number of vehicles, bicycles, and micromobility devices, package delivery location, and other demographic and transportation-related information.

Citywide Mobility Survey (CMS) Vehicle table contains characteristics of each vehicle in the participant’s household.

The Citywide Mobility Survey (CMS) is NYC DOT's annual travel survey to assess the travel behavior, preferences, and attitudes of NYC residents. It is composed of 5 linked data tables - this one is the 2019 CMS Household Survey.

In 2012, the IDB approved a project to support the preparation of a comprehensive public transport system for the metropolitan area of ​​La Paz and El Alto. The project included technical, legal, economic, social and environmental studies. One component was an urban mobility survey, which constitutes the main source of data for the present analysis. Within this framework, we gathered information on the travel patterns and socioeconomic characteristics of residents in June and July 2015. To obtain comparable data and to determine the most common trips, such as from home to work or school and back, we collected data from 6 p.m. to 9 p.m. on weekdays and weekends. The sample was collected at the sub-district level (blocks) to cover the districts of La Paz and El Alto, following a random selection process (see Annex 2 for more details). A total of 6,720 inhabitants of La Paz (4,208) and El Alto (2,512) were interviewed from a total of 6,208 households (3,892 and 2,316 in La Paz and El Alto respectively). Participants were surveyed about the last two trips they had made prior to the interview date.

Analysis of ‘Citywide Mobility Survey - Household Survey 2019’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/98ea2f14-d7fd-436a-8e4a-804197778e9c on 27 January 2022.

--- Dataset description provided by original source is as follows ---

The Citywide Mobility Survey (CMS) is NYC DOT's annual travel survey to assess the travel behavior, preferences, and attitudes of NYC residents. It is composed of 5 linked data tables - this one is the 2019 CMS Household Survey.

--- Original source retains full ownership of the source dataset ---

Abstract

Previous surveys on labor migration from Pacific Island countries are often cross-sectional, not readily available, and focusing on one migration scheme, country, or issue and hence incompatible. Such limitation of existing data restricts analysis of a range of policy-relevant issues that present themselves over the migrants' life cycle such as those on migration pathways, long-term changes in household livelihood, and trajectory of migrants’ labor market outcomes, despite the significant impacts of labor migration on the economy of the Pacific Island countries. To address these shortfalls in the Pacific migration data landscape, the PLMS is designed to be longitudinal, spanning multiple labor sending and receiving countries and collecting omnibus information on both migrants, their households and non-migrant households. The survey allows for disaggregation and reliable comparative analysis both within and across countries and labor mobility schemes. This open-access and high-quality data will facilitate more research about the Pacific migration, help inform and improve Pacific migration policy deliberations, and engender broader positive change in the Pacific data ecosystem.

Geographic coverage

Tonga: Tongatapu, ‘Eua, Vava’u, Ha’apai, Ongo Niua. Vanuatu: Malampa, Penama, Sanma, Shefa, Tafea, Torba. Kiribati: Abaiang, Abemama, Aranuka, Arorae, Banaba, Beru, Butaritari, Kiritimati, Maiana, Makin, Marakei, Nikunau, Nonouti, North Tabiteuea, North Tarawa, Onotoa, South Tabiteuea, South Tarawa, Tabuaeran, Tamana, Teraina.

Analysis unit

• Households in Kiribati, Tonga, and Vanuatu.
• Temporary migrant workers from Kiribati, Tonga and Vanuatu who participated in the Pacific Australia Labour Mobility scheme in Australia and the Recognised Seasonal Employers scheme in New Zealand

Kind of data

Sample survey data [ssd]

Sampling procedure

Sampling frame: The PLMS sample was designed based on a Total Survey Error framework, seeking to minimize errors and bias at every stage of the process throughout preparation and implementation.

The worker sample frame is an extensive list of approximately 11,600 migrant workers from Kiribati, Tonga and Vanuatu who had participated in the RSE and PALM schemes. Due to the different modes of interviews, sampling strategies for the face-to-face segment of the household survey in Tonga was different from the rest of the surveys implemented via phone interviews. The face-to-face segment of the household survey selected households using Probability Proportional to Size sampling based on the latest population census listing and our worker sample frame, with technical inputs from the Tonga Statistics Department. The phone-based segment of the household survey used a combination of Probability Proportional to Size sampling based on the existing sample frame and random digit dialing. The design of the sample benefited from technical inputs from the Tonga Statistics Departments and the Vanuatu National Statistics Office, as well as World Bank staff from Kiribati.

As participation in the survey is voluntary, a worker might agree to participate while their household did not, and vice versa. Because of this, the survey did not achieve a complete one-to-one match between interviewed workers and sending households. Of all interviewed respondents, 418 workers in the worker survey are linked to their households in the household survey. However, after removing incomplete interviews, 341 worker-household pairs remain. They are matched by either pre-assigned serial ID numbers or contact details collected in the household and worker surveys during the post-fieldwork data cleaning process.

Sampling deviation

The survey was originally planned to be conducted face-to-face and was so for most of the collection of household data in Tonga. However, due to COVID-19, it was switched to phone-based mode and the survey instruments were adjusted accordingly to better suit the phone-based data collection while ensuring data quality. In particular, the household questionnaire was shortened, and sampling strategy changed to a combination of Probability Proportional to Size sampling based on the existing household listing and random digit dialing.

Compared to in-person data collection, the usual caveats of potential biases in phone-based survey related to disproportional phone ownership and connectivity apply here. The random digit dialing approach provides data representative of the phone-owning population. Yet due to lack of information, it is difficult to judge whether sending households in Kiribati, Tonga, and Vanuatu are more or less likely to own a phone and/or respond positively to survey request than non-sending households.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

• The questionnaires were jointly designed in English by the World Bank and researchers at the Development Policy Centre, Australian National University. They were translated into Bislama, Gilbertese and Tongan, scripted into CAPI/CATI programs, tested and piloted before being finalized. The design of the questionnaires and the samples benefited from technical inputs from the Tonga Statistics Departments, Pacific consultants, and academic experts specialized in Pacific labor mobility and remittances.
• Enumerators are native speakers from the labor-sending countries covered in the survey and were trained to elicit information asked in the questionnaire in local languages.
• The phone-based household questionnaire is moderately shorter than the in-person version.

Cleaning operations

The published data have been cleaned and anonymized. All incomplete interview records have been removed from the final datasets. The anonymization process followed the theory of Statistical Disclosure Control for microdata, aiming to minimize re-identification risk, i.e. the risk that the identity of an individual (or a household) described by a specific record could be determined with a high level of confidence. The anonymization process employs the k-anonymity method to calculate the re-identification risk. Risk measurement, anonymization and utility measurement for the PLMS were done using sdcMicro, an add-on package for the statistical software R for Statistical Disclosure Control (SDC) of microdata.

Since the household questionnaire was shortened when the survey switched from face-to-face to phone-based data collection, there face-to-face datasets and phone-based datasets are not identical, but they are consistent and can be harmonized. The mapping guide enclosed in this publication provides a guide to data users to wish to harmonize them.

Household expenditure variables in the household dataset and individual wage variable in the household member dataset are in USD. Local currencies were converted into USD based on the following exchange rates: 1 Tongan Pa'anga= 0.42201412 USD; 1 Vanuatu Vatu= 0.0083905322 USD; 1 Kiribati dollar= 0.66942499 USD.

Response rate

Face-to-face segment of the PLMS household survey: not applicable. Phone-based segment of the PLMS household survey: 26%. The PLMS Worker survey: 31%

Citywide Mobility Survey (CMS) Person table contains characteristics of individual members of the participant’s household, including age, race, gender, disability status, education, employment, remote work, typical commute mode, biking frequency, shared services, and other demographic and transportation-related information.

This table provides statistical information about people in Canada by their demographic, social and economic characteristics as well as provide information about the housing units in which they live.

The Florida Department of Transportation (FDOT or Department) has identified processed, authoritative datasets to support the preliminary spatial analysis of equity considerations. These processed datasets are available at larger geographies, such as the United States Census Bureau tract or county-level; however, additional raw datasets from other sources can be used to identify equity considerations. Most of this raw data is available at the Census block group, parcel, or point-level—but additional processing is required to make suitable for spatial analysis. For more information, contact Dana Reiding with the FDOT Forecasting and Trends Office (FTO). The American Community Survey (ACS) Median Household Income Variables – Boundaries layer is identified to support the equity community indicator of income and poverty. This layer contains the most current release of data from the ACS about median household income by race and by age of householder. These are 5-year estimates shown by tract, county, and state boundaries. The layer is owned and managed by the ESRI Demographics Team. Data Link: https://www.arcgis.com/home/item.html?id=45ede6d6ff7e4cbbbffa60d34227e462 Available Geography Levels: State, County, Tract Owner/Managed By: ESRI Demographics FDOT Point of Contact: Dana Reiding, ManagerForecasting and Trends OfficeFlorida Department of TransportationDana.Reiding@dot.state.fl.us605 Suwannee Street, Tallahassee, Florida 32399850-414-4719

Datasource: Statistics Canada. 2013. National Household Survey (NHS) Profile. 2011 National Household Survey. Statistics Canada Catalogue no. 99-004-XWE. Ottawa. Released September 11, 2013. http://www12.statcan.gc.ca/nhs-enm/2011/dp-pd/prof/index.cfm?Lang=E http://www12.statcan.gc.ca/nhs-enm/2011/dp-pd/prof/index.cfm?Lang=E (accessed October 9, 2014). Statistics Canada. 2014. 2011 Semi-custom Profile of Yukon Territory and Selected Regions, 2011 National Household Survey. Ottawa. February 20, 2014. Footnotes: A value of 0 in any given cell represents one of the following: 1) value is actually zero; 2) value may be random rounded to zero; or 3) value is more than zero but is http://www12.statcan.gc.ca/nhs-enm/2011/dp-pd/prof/help-aide/aboutdata-a... suppressed for confidentiality reasons. Values have been subjected to a confidentiality procedure known as http://www12.statcan.gc.ca/nhs-enm/2011/dp-pd/prof/help-aide/aboutdata-a... random rounding For Statistics Canada's definition of terms, http://www12.statcan.gc.ca/nhs-enm/2011/ref/dict/azindex-eng.cfm click here

The community profiles contain data from 2016 Census and long form program. The 2016 census data is considered to be of good quality and general comparisons can be made with similar data from previous years. Direct comparisons cannot be made between Statistics Canada’s 2016 Long Form data and the 2011 National Household Survey (NHS).The figures shown in the tables and charts have been subjected to a confidentiality procedure known as random rounding to prevent the possibility of associating statistical data with any identifiable individual. Under this method, all figures, including totals and margins, are randomly rounded either up or down to a multiple of "5", and in some cases "10". While providing strong protection against disclosure, this technique does not add significant error to the data. The user should be aware that totals and margins are rounded independently of the cell data so that some differences between these and the sum of rounded cell data may exist. Also, minor differences can be expected in corresponding totals and cell values among various census tabulations.Statistics Canada is committed to protect the privacy of all Canadians and the confidentiality of the data they provide. As part of this commitment, some population counts of geographic areas are adjusted in order to ensure confidentiality.For more information about Kingston's Community & Neighbourhood Profiles, as well as links to exciting new tools, please visit our website: https://www.cityofkingston.ca/explore/neighbourhood-profilesA detailed Glossary of Terms is also available (Adobe PDF format): https://drive.google.com/file/d/1KAbrqmARXjzy1yBcVlVYf2Xz-KidOfXM/view?usp=sharing

The Mobility Survey (010930) is a statistical operation whose objective is to quantify the working-day mobility of the population residing in the Basque Country, as well as the characterization and motivation of travel. The collection of information has been carried out through interviews with all the homes that make up the sample and information has been collected from all residents in the household aged 7 and over. The field phase took place between October 2021 and March 2022.

The Nationwide Personal Transportation Survey serves as the nation's inventory of daily personal travel. It collects data on daily trips including purpose of the trip, means of transportation used, travel time, vehicle occupancy, driver characteristics, and vehicle attributes. These data are collected for all personal trips, all modes and purposes, all trip lengths, all areas of the country, all days of the week, and all months of the year. Part 1, the Household File, contains data on the relationship between household members and demographic information for household members. The file also contains information on housing characteristics, as well as characteristics of the block group and census tract. Availability and distance to public transportation are also included. Part 2, the Person File, contains information on seat belt use, modes of transportation used for travel to work, and costs for parking. Part 3, the Vehicle File, contains data relating to each of the household's vehicles, including whether a particular household member usually drives the vehicle, when it was purchased, the vehicle type, and model year. Part 4, the Travel Day Trip File, contains data about each trip the person made on the household's randomly assigned travel day. Information was collected on the purpose of the trip, the number of trips within the trip chain, where the trip chain started, and the amount of time spent at each destination. Part 5, the Segmented Travel Day Trip File, contains data for up to four segments of each segmented travel day trip the person made on the travel day. The file contains information on the start time, mode of transportation used, purpose, and duration of each travel segment. Part 6, the Travel Period File, contains data for every trip of at least 75 miles one way that the person took during a 14-day period ending on the travel day. The file contains information on the start date, purpose, and transportation mode used for trip. New for the 1995 survey was a written diary, used to help respondents to better remember their travel on their designated travel day, and a household roster of trips, which was used to assist respondents in recalling trips made with other household members. New questions included satisfaction with the nation's transportation system, reactions to mobility and congestion, perceived difficulties in travel, and use of seat belts.

Additional file 1. The table with information about origin-destination pairs by a total of hours, motivation, and type of zone destination and the pdf file with the quantitative description of mobility motivation.

Created by Statistics Canada. Statistics are for Surrey only and are broken down to a community level. Please note that Statistics Canada has divided their information into main two tables (2011 Census and 2011 National Household Survey). This table is the 2011 National Survey portion. For further information please click here.

The National Household Survey (NHS) was conceived to replace the mandatory long-form census questionnaire. The content of the NHS 2011 is similar to the past long-form questionnaire, although some questions and sections have changed. NHS Data Tables provide statistical information about people in Canada by their demographic, social and economic characteristics as well as information about the housing units in which they live. Geography levels include: 1) Canada, provinces and territories 2) Census metropolitan areas and census agglomerations

Additional file 3. The dataset used to conduct the analysis.

Abstract

The UNHCR Results Monitoring Surveys (RMS) is a household-level survey on people with and for whom UNHCR works or who benefit from direct or indirect assistance provided by UNHCR, including refugees and asylum seekers, internally displaced persons, returnees, stateless and others of concern. The objective of the survey is to monitor impact and outcome level indicators on education, healthcare, livelihoods, protection concerns, shelter, and water and sanitation. The results contribute to an evidence base for reporting against UNHCR's multi-year strategies to key stakeholders. This RMS took place in Guatemala in July 2022 at national level.

Analysis unit

Household and individual

Kind of data

Sample survey data [ssd]

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire contained the following sections: Survey Information , Socio-economic Indicators & Mobility, Information on the well-being of the household, Habitable and affordable housing, Habitable housing and access to basic services, Health Services and Social Protection, Perceptions on safety and gender-based violence.

Monitoring the effects of tariff raises in public transport within the framework of the general mobility developments. This description comprises the tenth wave of the longitudinal mobility survey ( longitudinaal verplaatsingsonderzoek ). Preceding waves are stored under different study numbers. The survey monitors ( changes in ) transportational behaviour, mobility and effects of raising tariffs for public transportation. Data were gathered by questionnaire. Diaries were used for describing all mobility during one week. Detailed data were gathered on: family composition, financial situation of family, working hours, commuting, travelling allowances, car, train, use of reduced fare cards for public transport. Moving to another home and factors influencing this. Use of train in preceding week, month, half year and year. Change in place of work last three years and factors influencing this. Parking facilities near place of work, use of public transportation in commuting, attitude regarding public transport and ownership and use of Pas 65 ( reduction card for the aged ). This wave proper consists of seven files, containing family-data( A=SPSS-file, D=raw data ), family member-data ( B=SPSS-file, E=raw data ), transfer-data ( C=raw data ), week-matrices ( F=raw data ), and commuting data ( G=raw data ) respectively. It contains two extra cumulative files. One contains the most relevant variables from all March-waves of all respondents ever participating ( P1015H ). The second ( P1045J ) uses cars owned by panel-members as units of analysis and contains car-related variables and costs analysis. Moreover this wave contains two general SPSS-setup files, to be used for analyzing the week- matrices and commuting-data files of all waves ( P1045K and P1045L ). General hard-copy documentation relevant to all preceding waves is also stored under this number. Background variables: basic characteristics/ residence/ household characteristics/ occupation/employment/ income/capital assets/ education/ consumption of durables