The Project Canada Research Program has been carried out from the "https://www.ulethbridge.ca/" Target="_blank">University of Lethbridge. National surveys of adults 18 and over have been conducted in 1975, 1980, 1985, 1990, and 1995. Adult surveys in 2000 will complete the program. The goal has been to generate extensive information on life in Canada, with specific attention given to social issues, intergroup relations, and religion.

The AGRI National Project (ANP) was a three-year longitudinal study conducted by a multi-institute research team based at the Alberta Gambling Research Institute (AGRI). The aim of the study was to capture a national-wide picture of gambling and problem gambling in Canada. The ANP had ten research objectives. The Online Panel Study was one of three parts of the ANP and was central to many of the ten objectives. The aims of the study included but was not limited to: Determine provincial and demographic differences in gambling and problem gambling; Determine the prevalence of online gambling; and Determine the use of and perceived effectiveness of harm minimization initiatives in preventing problem gambling. The Online Panel Study collected data on several gambling-specific aspects of the responders' lives. The data contains gambling-specific information including: Demographics; Gambling attitudes and beliefs in gambling fallacies; Gambling participation; and Family history of problem gambling; In addition to gambling-specific data, the Online Panel Study contains general data variables including: Psychological factors (personality, mental health); and Comorbid factors (behavioural addictions, substance use, PTSD) A sample of 10,199 participants were recruited from each province of Canada. Participants were recruited through the Leger Opinion's registered pool of online participants. The LEO participant pool is structured to be demographically and geographically representative of the Canadian adult (18 years and older) population. Of the initial 10,199 participants, 4,707 participated in the follow-up survey. LEO registered participants were sent an email asking if they participated in gambling activities once per month. Participants who did gamble and consented to participating in the study were directed to an online survey. The baseline data was collected between August 2018 and October 2018. The follow-up data was collected between August 2019 and November 2019. Additional information on sampling, retention, study variables, and survey questionnaires can be located in the accompanying user manual and codebooks. The manual and codebooks were created by Dr. Carrie A. Shaw (née Leonard)

The Survey of Labour and Income Dynamics (SLID) is a Statistics Canada survey intended for use in research on changes over time in Canadians labour force activity status and economic well-being. Two major characteristics of the survey design result directly from this objective. First, SLID is a longitudinal survey; each panel participates in the survey for six years. Second, SLID focuses on whole households, and the range of subjects that it covers is broad enough to allow for the collection of data on family situations and major demographic events. This aspect of the survey enables researchers to examine the links between demographic events, labour force activity patterns and income. The longitudinal job file focuses on wages, work schedules, length of employment etc. The Survey of Labour and Income Dynamics (SLID) is a longitudinal household survey conducted by Statistics Canada. It is designed to capture changes in the economic well-being of individuals and families over time and the determinants of their well-being. Individuals originally selected for the survey are interviewed once or twice per year for six years to collect information about their labour market experiences, income and family circumstances. In order to obtain complete information on families and to obtain cross-sectional data, people who live with the original respondents at any time during the six years are also interviewed during the time of cohabitation.

The Canadian Perspectives Survey Series (CPSS) is a set of short, online surveys beginning in March 2020 that will be used to collect information on the knowledge and behaviours of residents of the 10 Canadian provinces. All surveys in the series will be asked of Statistics Canada’s probability panel. The probability panel for the CPSS is a new pilot project initiated in 2019. An important goal of the CPSS is to directly collect data from Canadians in a timely manner in order to inform policy makers and be responsive to emerging data needs. The CPSS is designed to produce data at a national level (excluding the territories). The survey program is sponsored by Statistics Canada. Each survey in the CPSS is cross sectional. Participating in the probability panel and the subsequent surveys of the CPSS is voluntary. The third survey of the CPSS is CPSS3 – Resuming Economic and Social Activities During COVID-19. It was administered from June 15, 2020 until June 21, 2020.

Abstract

In order to develop various methods of comparable data collection on health and health system responsiveness WHO started a scientific survey study in 2000-2001. This study has used a common survey instrument in nationally representative populations with modular structure for assessing health of indviduals in various domains, health system responsiveness, household health care expenditures, and additional modules in other areas such as adult mortality and health state valuations.

The health module of the survey instrument was based on selected domains of the International Classification of Functioning, Disability and Health (ICF) and was developed after a rigorous scientific review of various existing assessment instruments. The responsiveness module has been the result of ongoing work over the last 2 years that has involved international consultations with experts and key informants and has been informed by the scientific literature and pilot studies.

Questions on household expenditure and proportionate expenditure on health have been borrowed from existing surveys. The survey instrument has been developed in multiple languages using cognitive interviews and cultural applicability tests, stringent psychometric tests for reliability (i.e. test-retest reliability to demonstrate the stability of application) and most importantly, utilizing novel psychometric techniques for cross-population comparability.

The study was carried out in 61 countries completing 71 surveys because two different modes were intentionally used for comparison purposes in 10 countries. Surveys were conducted in different modes of in- person household 90 minute interviews in 14 countries; brief face-to-face interviews in 27 countries and computerized telephone interviews in 2 countries; and postal surveys in 28 countries. All samples were selected from nationally representative sampling frames with a known probability so as to make estimates based on general population parameters.

The survey study tested novel techniques to control the reporting bias between different groups of people in different cultures or demographic groups ( i.e. differential item functioning) so as to produce comparable estimates across cultures and groups. To achieve comparability, the selfreports of individuals of their own health were calibrated against well-known performance tests (i.e. self-report vision was measured against standard Snellen's visual acuity test) or against short descriptions in vignettes that marked known anchor points of difficulty (e.g. people with different levels of mobility such as a paraplegic person or an athlete who runs 4 km each day) so as to adjust the responses for comparability . The same method was also used for self-reports of individuals assessing responsiveness of their health systems where vignettes on different responsiveness domains describing different levels of responsiveness were used to calibrate the individual responses.

This data are useful in their own right to standardize indicators for different domains of health (such as cognition, mobility, self care, affect, usual activities, pain, social participation, etc.) but also provide a better measurement basis for assessing health of the populations in a comparable manner. The data from the surveys can be fed into composite measures such as "Healthy Life Expectancy" and improve the empirical data input for health information systems in different regions of the world. Data from the surveys were also useful to improve the measurement of the responsiveness of different health systems to the legitimate expectations of the population.

Kind of data

Sample survey data [ssd]

Sampling procedure

POSTAL

1,487 named individuals were selected from the Karom Group of Companies, Dialogue Canada household mail panel. This mail panel includes a cross-section of Canadians, with the exception of those living in the Yukon, Northwest Territories or Nunavut, from which a sample can be obtained to represent the Canadian population according to the most recent Statistics Canada data. The panel file was stratified by regions in Canada: city size, French Quebec and rest of Canada and ordered by postcode. The 1,487 named individuals were selected from the Dialogue Mail panel file, using a random method on the sample sorted by postcode.

Individual members of each household who were asked to complete the survey were identified by birth date and gender with this identifying information.

From the initial 1,487 mailed out, 816 questionnaires came back hence reaching a response rate of 55%.

CATI

The sample was drawn in such a way that it represented the Canadian population with the exception of the Canadians living in the Yukon, Northwest Territories or Nunavut.

The sampling model relied on the stratification of the population by ten provinces and by six community sizes. Telephone numbers were selected from the most recently published telephone directories. These numbers acted as "seeds" from which the sample was actually generated. The original "seed" telephone numbers were not used in the sample. Both unlisted numbers and numbers listed after the directory publication are included in the sample.

From within each household contacted, respondents 18 years of age and older were screened for random selection using the most recent birthday method.

From the 12,350 total calls made, 778 calls completed the interview. Among the 12,350 calls, 8,466 were ineligibles and from the latter, 5,305 calls for which the respondent was unavailable. The net response rate is therefore 24.6%.

Mode of data collection

Mail Questionnaire [mail]

Cleaning operations

Data Coding At each site the data was coded by investigators to indicate the respondent status and the selection of the modules for each respondent within the survey design. After the interview was edited by the supervisor and considered adequate it was entered locally.

Data Entry Program A data entry program was developed in WHO specifically for the survey study and provided to the sites. It was developed using a database program called the I-Shell (short for Interview Shell), a tool designed for easy development of computerized questionnaires and data entry (34). This program allows for easy data cleaning and processing.

The data entry program checked for inconsistencies and validated the entries in each field by checking for valid response categories and range checks. For example, the program didn’t accept an age greater than 120. For almost all of the variables there existed a range or a list of possible values that the program checked for.

In addition, the data was entered twice to capture other data entry errors. The data entry program was able to warn the user whenever a value that did not match the first entry was entered at the second data entry. In this case the program asked the user to resolve the conflict by choosing either the 1st or the 2nd data entry value to be able to continue. After the second data entry was completed successfully, the data entry program placed a mark in the database in order to enable the checking of whether this process had been completed for each and every case.

Data Transfer The data entry program was capable of exporting the data that was entered into one compressed database file which could be easily sent to WHO using email attachments or a file transfer program onto a secure server no matter how many cases were in the file. The sites were allowed the use of as many computers and as many data entry personnel as they wanted. Each computer used for this purpose produced one file and they were merged once they were delivered to WHO with the help of other programs that were built for automating the process. The sites sent the data periodically as they collected it enabling the checking procedures and preliminary analyses in the early stages of the data collection.

Data quality checks Once the data was received it was analyzed for missing information, invalid responses and representativeness. Inconsistencies were also noted and reported back to sites.

Data Cleaning and Feedback After receipt of cleaned data from sites, another program was run to check for missing information, incorrect information (e.g. wrong use of center codes), duplicated data, etc. The output of this program was fed back to sites regularly. Mainly, this consisted of cases with duplicate IDs, duplicate cases (where the data for two respondents with different IDs were identical), wrong country codes, missing age, sex, education and some other important variables.

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A dataset, 1970-2009, containing equivalently defined variables for the British Household Panel Study (BHPS), the Household Income and Labour Dynamics in Australia (HILDA), the Korea Labor and Income Panel Study (KLIPS) (new this year), the Panel Study of Income Dynamics (PSID), the Russia Longitudinal Monitoring Survey (RLMS-HSE) (new this year), the Swiss Household Panel (SHP), the Canadian Survey of Labour and Income Dynamics (SLID), and the German Socio-Economic Panel (SOEP). The data are designed to allow cross-national researchers not experienced in panel data analysis to access a simplified version of these panels, while providing experienced panel data users with guidelines for formulating equivalent variables across countries. The CNEF permit researchers to track yearly changes in the health and economic well-being of older people relative to younger people in the study countries. The equivalent file provides a set of constructed variables (for example pre- and post-government income and United States and international household equivalence weights) that are not directly available on the original surveys. Since the Cross-National Equivalent File 1970-2009 can be merged with the original surveys, PSID-CNEF users can easily incorporate these constructed variables into current analyses. The most recent release of the Equivalent File includes: * BHPS data from 1991 to 2005 on over 21,000 individuals and approximately 6,000 households. * GSOEP data from 1984 to 2007 on over 20,000 individuals and approximately 6,000 households in Germany. * HILDA data from 2001 to 2006 on over 19,000 individuals and 7,000 households. * PSID data from 1980 to 2005 on over 33,000 individuals and approximately 7,000 households. * SHP data from 1999 to 2006 on 12,900 individuals and 5,000 households. * SLID data from 1993 to 2006 on over 95,000 individuals and approximately 32,000 households. With one exception, the CNEF country data are available on CD-ROM from Cornell University for a fee. The Canadian SLID data are not distributed on the CD but are available to CNEF registered researchers through special arrangements with Statistics Canada. Complete instructions for obtaining CNEF data may be accessed on the project website. * Dates of Study: 1980-2007 * Study Features: International, Longitudinal * Sample Size: ** BHPS: 21,000+ ** PSID: 33,000+ ** SLID: 95,000+ ** GSOEP: 20,000+ ** HILDA: 19,000+ ** SHP: 12,900+ NACDA link: http://www.icpsr.umich.edu/icpsrweb/NACDA/studies/00145/detail

The AGRI National Project (ANP; https://research.ucalgary.ca/alberta-gambling-research-institute/research/national-gambling-study) provided an unparalleled opportunity for the investigation of how gambling in Canada had been impacted by COVID. While the ANP Online Panel was intended to capture Canada-wide gambling and problem gambling, while accounting for the inter-provincial variation in legal gambling provision, the ANP COVID Online Panel was designed to extend this examination to include the impact of the COVID-19 pandemic social and economic restrictions on gambling and problem gambling. To examine the impact of the pandemic on gambling in Canada, we extended the ANP Online Panel Study, conducting two additional data collection waves. This two-wave panel study was administered by Leger and re-recruited AGRI National Project Online Panel participants. As such, the ANP online panel follow-up survey data became the baseline data for this study. For the first wave of data collection, COVID Wave 1, recruitment from ANP Online Panel follow-up participants (n = 4707), was conducted expeditiously (May 14th – June 1st, 2020). Data collection began one month after the nation-wide ‘lockdown’ began and concluded while all of the provinces were still enforcing these widespread social and economic restrictions. A total of n = 3449 participants completed the COVID Wave 1 survey. Six-months later, the COVID Wave 2 recruitment began, and participants who had completed the COVID Wave 1 survey were invited to participate. The COVID Wave 2 data collection period took place between the 1st and 20th of December 2020, after the easement of nation-wide COVID restrictions. During this Wave 2 data collection period however, while the nation-wide lockdown was repealed, many provinces were still instituting some restrictions. Gambling venues for example, were open but reduced capacity to adhere to social distancing space requirements. Nonetheless, the COVID Wave 2 data collection was designed to determine what pandemic lockdown related changes were enduring. Furthermore, together with the ANP Online Panel follow-up data as a baseline, this study becomes an ABA design, with a large and stratified sample. COVID Wave 2 data, as an added benefit, provides the AGRI National Project with an appropriately timed third annual data collection. Additional information on sampling, retention, study variables, and survey questionnaires can be located in the accompanying user manual and codebooks. The manual and codebooks were created by Rokelle T. Shaw and Carrie A. Shaw.

The Canadian Perspectives Survey Series (CPSS) is a set of short, online surveys beginning in March 2020 that will be used to collect information on the knowledge and behaviours of residents of the 10 Canadian provinces. All surveys in the series will be asked of Statistics Canada’s probability panel. The probability panel for the CPSS is a new pilot project initiated in 2019. An important goal of the CPSS is to directly collect data from Canadians in a timely manner in order to inform policy makers and be responsive to emerging data needs. The CPSS is designed to produce data at a national level (excluding the territories). The survey program is sponsored by Statistics Canada. Each survey in the CPSS is cross sectional. Participating in the probability panel and the subsequent surveys of the CPSS is voluntary. The first survey of the CPSS is CPSS1 – Impacts of COVID-19. It was administered from March 29, 2020 until April 3, 2020.

The Canadian Out-of-Employment Panel Survey was conducted by Statistics Canada for Human Resources Development Canada, Strategic Evaluation and Monitoring. This survey interviewed people who had a job interruption during one of the two reference periods: (1) Jan. 29-Mar. 11, 1995; or (2) Apr. 23-June 3, 1995.The survey gathered information on subsequent employment during a 13-month period, background demographics on the individual and the household, as well as information on job search activities and outcomes, income, assets and debts, expenditures, and training.In 1996, the COEP survey was re-designed as the Changes in Employment Survey, referred to as COEP 1996. The re-designed survey had changes in the sample design and content to allow a more complete picture of the population of individuals experiencing a loss or change of employment. The survey collects information on employment history during an 18-month period, background demographics on the individual and the household, as well as information on job search activities and outcomes, income, assets and debts, expenditures, and training.The main changes to the sample design compared to COEP 1995 are as follows: all individuals who are issued an ROE in the reference period are included in the 1996 design whereas under the 1995 design, only individuals whose ROE was issued for particular reasons were included; and the reference periods for the 1996 design are consecutive quarters, giving complete coverage across time whereas for the 1995 design, two discrete time periods were selected.The main change to the content compared to COEP 1995 is as follows: information is collected about all employers the individual worked for during the reference period whereas under the 1995 design, information was only collected for the ROE employer, the next employer and the current employer.

This study utilized: a national survey of law enforcement officials; a national survey of criminal justice faculty; a survey of criminal justice students at Arizona State University, Kutztown University, Michigan State University, and Sam Houston State University; four separate surveys of a small expert panel; and mini-case studies to investigate issues associated with police human resource management and planning, such as recruitment, selection, training, and promotion.

These data were collected through an online panel-based survey. The survey was designed to better understand Canadian beef producers grazing practices (continuous, rotational or adaptive such as Holistic Management, Adaptive Multipaddock or regenerative grazing), their reported well-being, mindsets (management priorities, systems thinking, etc) and demographics. The panel was recruited and run by Kynetec which is a specialist agricultural polling firm, who recruited for the study from their proprietary Canadian Producer Database. The survey was stratified across the four largest beef-producing provinces, roughly proportionally to farm numbers: Alberta (n=85), Saskatchewan (n=45), Manitoba (n=35) and Ontario (n=35). No criteria were applied on the amount of beef production, and respondents could also have other commodities. However, all participants had to be over 18, either the sole or joint decision-maker on their property (not secondary), have beef as part of their gross farm sales in 2018, and they had to graze cattle rather than simply feed them. Participants were rewarded with $25. Confidence interval is estimated at 6.9%.The dataset contains two files: the study questionnaire (text) and survey responses (tabular).

The Canadian Perspectives Survey Series (CPSS) is a set of short, online surveys beginning in March 2020 that will be used to collect information on the knowledge and behaviours of residents of the 10 Canadian provinces. All surveys in the series will be asked of Statistics Canada’s probability panel. The probability panel for the CPSS is a new pilot project initiated in 2019. An important goal of the CPSS is to directly collect data from Canadians in a timely manner in order to inform policy makers and be responsive to emerging data needs. The CPSS is designed to produce data at a national level (excluding the territories). The survey program is sponsored by Statistics Canada. Each survey in the CPSS is cross sectional. Participating in the probability panel and the subsequent surveys of the CPSS is voluntary. The second survey of the CPSS is CPSS2 – Monitoring the Effects of COVID-19. It was administered from May 4, 2020 until May 10, 2020.

The Canadian Perspectives Survey Series (CPSS) is a set of short, online surveys beginning in March 2020 that will be used to collect information on the knowledge and behaviours of residents of the 10 Canadian provinces. All surveys in the series will be asked of Statistics Canada’s probability panel. The probability panel for the CPSS is a new pilot project initiated in 2019. An important goal of the CPSS is to directly collect data from Canadians in a timely manner in order to inform policy makers and be responsive to emerging data needs. The CPSS is designed to produce data at a national level (excluding the territories). The survey program is sponsored by Statistics Canada. Each survey in the CPSS is cross sectional. Participating in the probability panel and the subsequent surveys of the CPSS is voluntary. The sixth survey of the CPSS is CPSS6 – Substance Use and Stigma during the Pandemic. It was administered from January 25, 2021 until January 31, 2021.

The City of Toronto's Open Government Committee and senior staff promote an organizational culture of greater collaboration and openness. In 2015, the committee engaged with Ipsos Reid to conduct a survey to learn more about the views City of Toronto residents have on Open Government. 1,549 residents participated in the survey. These residents were selected from Ipsos Reid's online panel.

Statistics Canada publishes monthly labour force statistics for all Canadian Census Metropolitan Areas (CMAs) and provinces. In addition, the City of Toronto purchases a special run from Statistics Canada of Labour Force Survey (LFS) data for city of Toronto residents (i.e. separate from the rest of the Toronto CMA). LFS data are collected by place of residence, and therefore city of Toronto's "employment" represents "employed residents" and not "jobs" in the city of Toronto. There are more jobs in the city of Toronto than employed city of Toronto residents. In this LFS database, you will find 22 monthly tables and 28 annual tables. Most of the tables contain data for five geographies: city of Toronto, Toronto CMA, Toronto/Hamilton/Oshawa CMAs, Ontario and Canada ( see attachment Table of Contents below a full description ). LFS data in the IVT tables are not seasonally adjusted. Top level seasonally adjusted LFS data are available in our monthly Toronto Economic Bulletin on Open Data. LFS is based on a monthly sample of approximately 2,800 households in the Toronto CMA, about half of the sample is from the city of Toronto; therefore, estimates will vary from the results of a complete census. LFS follows a rotating panel sample design, in which households remain in the sample for six consecutive months. The total sample consists of six representative sub-samples of panels, and each month a panel is replaced after completing its six month stay in the survey. Outgoing households are replaced by households in the same or similar area. This results in a five-sixths month-to-month sample overlap, which makes the design efficient for estimating month-to-month changes. The rotation after six months prevents undue respondent burden for households that are selected for the survey ( see attachment Guide to the Labour Force Survey for more information). Upon reviewing the data, you will see that at least some cells in the IVT tables have been suppressed. For confidentiality reasons, Statistics Canada suppresses Labour Force Survey data for any cell that corresponds to less than 1,500 persons. At the beginning of 2015, Statistics Canada substantially changed the methodology used to produce LFS population estimates for the city of Toronto. These changes have resulted in large and inexplicable swings in population and related counts, which are not real. However, the unemployment and participation rates for city residents showed very little change in this revision. The red dots in the chart above represents Statistics Canada's Annual Demographics estimates for the populations of the city of Toronto, age 15 and over. These are only estimates, but they are generally accepted as the most accurate estimates for the city's population. (Source: https://www150.statcan.gc.ca/n1/pub/91-214-x/91-214-x2018000-eng.htm). The most recent Statistics Canada population estimate for the city of Toronto is for July 1, 2015; therefore, we have to use projections thereafter. There are several population projections for the city. The projection that EDC staff has chosen to use for rebasing city of Toronto LFS data is the Ontario Ministry of Finance Population Projections 2017-2041 and downloaded June, 2017 from http://www.fin.gov.on.ca/en/economy/demographics/projections/ Please see attachment Rebased Labour Force Survey for City of Toronto below for annual adjustment factors, monthly adjustment factors and an example of how to rebase the absolute numbers for the city of Toronto.

Health Canada commissioned Nanos Research to conduct a public opinion survey to support the use of citizen science to address government and departmental science and research priorities, as well as Open Science initiatives. A total of 4,702 Canadians were surveyed using an online panel and recruited to reflect the Canadian population. The online survey was conducted between March 16th and March 30th, 2023.

EKOS Research Associates and the Canada Millennium Scholarship Foundation conducted a monthly national study of the finances of post-secondary students from September 2001 until May 2002. The study was designed to capture the expenses and income of students on a monthly basis, in order to profile the financial circumstances of Canadian post-secondary students and the adequacy of available funding. The Web based Students Financial Survey provided accurate, quantifiable results for the first time on such issues as the incidence and level of assistance, the level of debt from outstanding bank loans, personal lines of credit, and credit cards. The study also yielded up-to-date information on student assets (such as automobiles, computers, and electronics), student earnings, time usage, and types of expenses incurred. The survey featured a panel of 1,524 post-secondary students from across the country, who participated in a very brief monthly survey, either via Internet or telephone. Students were required to complete a longer baseline wave of the survey in order to participate in the study. The baseline survey asked a number of questions concerning summer income and existing debt, including credit card debt. This dataset was received from the Canada Millennium Scholarship Foundation as is. Issues with value labels and missing values were discovered and corrected as best as possible with the documentation received. The variable gasst: Do you receive any government assistance? was not corrected due to lack of documentation about this variable. Some caution should be used with this dataset. This dataset was freely received from, the Canadian Millenium Scholarship Foundation. Some work was required for the variable and value labels, and missing values. They were correct as best as possible with the documentation received. Caution should be used with this dataset as some variables are lacking information.

The British Election Study Nine-Wave Panel Survey, 2005-2010 contains panel data from nine surveys conducted between the 2005 and 2010 general elections.

The nine waves were collected as follows: three waves in 2005, conducted before the election campaign, during the campaign and post-election; one wave conducted in 2006, one in 2008 and one in 2009; and three waves conducted in 2010, before the election campaign, during the campaign and post-election.

Further information is available from the BES Panel 2005-2010 webpage and the ESRC Performance Politics: The Dynamics of Political Support in Britain award webpage.

For the second edition (August 2014) data from waves 7-9 were added to the study and the documentation updated accordingly.

Background: Increasing numbers of variables in surveys and administrative databases are created. Principal component analysis (PCA) is important to summarize data or reduce dimensionality. However, one disadvantage of using PCA is the interpretability of the principal components (PCs), especially in a high-dimensional database. By analyzing the variance distribution according to PCA loadings and approximating PCs with input variables, we aim to demonstrate the importance of variables based on the proportions of total variances contributed or explained by input variables.Methods: There were five data sets of various sizes used to understand the performance of PC approximation: Hitters, SF-12v2 subset of the 2004–2011 Medical Expenditure Panel Survey (MEPS), and the full set of 1996–2011 MEPS data, along with two data sets derived from the Canadian Health Measures Survey (CHMS): a spirometry subset with the measures from the first trial of spirometry and a full data set that contained non-redundant variables. The variables in data sets were first centered and scaled before PCA. PCs were approximated through two approaches. First, the PC loadings were squared to estimate the variance contribution by variables to PCs. The other method was to use forward-stepwise regression to approximate PCs with all input variables.Results: The first few PCs had large variances in each data set. Approximating PCs using stepwise regression could efficiently identify the input variables that explain large portions of PC variances than approximating according to PCA loadings in the data sets. It required fewer numbers of variables to explain more than 80% of the PC variances through stepwise regression.Conclusion: Approximating and interpreting PCs with stepwise regression is highly feasible.PC approximation is useful to (1) interpret PCs with input variables, (2) understand the major sources of variances in data sets, (3) select unique sources of information, and (4) search and rank input variables according to the proportions of PC variance explained. This can be an approach to systematically understand databases and search for variables that are important to databases.