Friday, May 31, 2019

2016 Labour Force Survey - missing NOCs

A researcher is looking for NOC occupation groups for the monthly 2016 Labour Force Survey PUMFs.  Is this the way it should be represented: NOCS_01_25 STC Nesstar and NOCS_01_47 STC Nesstar when there actually are no such variables in 2016? 

Is it correct that the values are 100% missing for in 2016? It would be helpful to have NOC values for 2016.

What was the intention in 2016 when there are NOC values for the PUMF for these variables, e.g., on Odesi see January 2015: NOCS_01_25 link and NOC_01_47 link and for January 2017: NOC_10 LINK and NOC_40 LINK?  Would this be considered a problem with the data files?  

As an aside, there are SOC80_21 and SOC80_49 variables (with values) in 2015 and 2016.  Revisions to the 2015 LFS

Follow-Up Question:
I’d like to make a correction please to my question, with thanks to Scholars Portal for reviewing the occupation variables from 2015 – 2017 LFS monthly PUMFs.

Is it correct that there are supposed to be placeholders for a number of occupation variables but no data as highlighted in yellow  below?

  1. All the LFS monthly PUMFs, 1987-2015, have data for NOCS-01-25 and NOCS_01_47, but as for the variables SOC80_21 and SOC80_49, there is no data.  
  2. The monthly 2016 LFS PUMFs have  variables named NOCS_01_25, NOCS_01_47, SOC80_21 and SOC80_49 but with no data.
  3. The monthly 2017 LFS PUMFs have two occupation variables only, the new NOC_10 and NOC_40.

The short answer to this is simply that the labels have changed from the older years to the newer ones. For example, SOC80_21 was replaced with an NOC listing instead. From what I’ve been told, the descriptions of the variables should remain the same, it’s just a matter of needing to match them up from year to year (not necessarily the answer you were looking for I’m sure!)

So yes, it is correct that there is no data.

Thursday, May 30, 2019

Where are the PCCF Files?

I was looking for the most recent version of the PCCF which is supposed to be under MAD_PCCF_FCCP_DAM/ROOT/2019 but this directory does not show up (there are folders for 1986 all the way to 2018, but no 2019). Also, if I look under /MAD_PCCF_FCCP_DAM/Root/2018/pccf-fccp for the previous version, this folder is empty!

We moved it to reflect the most recent Census release! See attached. Sorry for the confusion!

*Original email included attachment*

PCCF Question - Rural vs Urban FSAs

I have a question from a grad student in Political Studies and, given my lack of expertise dealing with the PCCF, I thought I’d post it here for help. The problem stems largely from the fact that some FSAs are classified as both urban and rural.:

"I am using survey data to determine whether or not feelings of western alienation are higher in rural places relative to urban places in Western Canada. My survey asked respondents for the first three digits of their postal code (FSA), which I plan to code as either rural or urban. To do so, I plan on using the Postal Code Conversion File (PCCF) to code the FSAs of Western Canada as rural or urban, according to the "PopCntr_RA_size_class" variable. Unfortunately, each FSA has multiple values for the "PopCntr_RA_size_class" variable, making it difficult to code each FSA as either rural or urban. How can I effectively sort each FSA into the geographic categories?

Also, once I classify each FSA as rural or urban, how can I integrate that information into the survey data set? Is there a way to create an SPSS syntax file that sorts the respondents into geographic categories based on their reported FSA?"

I’ve received the following from subject matter: 

“There is no easy way to classify the FSAs as either rural/urban. FSAs are designed as part of Canada Post Corporation’s mail delivery system, which conceptually is operational, not geographical. That makes it difficult to match it with conceptually geographic systems, like StatCan’s census geographies. The PCCF does the best it can, and at the lowest levels of geography, it’s not too bad. However, moving to higher levels of geography, like Population Centres, or higher in the delivery system, like FSAs, causes more gray areas. To facilitate the sorting of a lot of mail, they cover delivery to many different types of geography: villages, indian reserves, cities, towns, rural routes, and so on. It is not surprising that they cannot be classified as either rural or uban.

The best that can be done is some analysis of how the FSAs link up with PopCentres in the PCCF. Then, the researcher will need to make some decisions as to how to define each FSA, based on that analysis.

So, given all that, we have done the following:

— selected all non-retired FSAs from the western provinces (Manitoba to British Columbia) à 455
— found those that overlapped more than 1 PopCentreSizeClass or more than 1 PopCentreRAType à 304

and then we provided further information on those with the postal code counts. See the attached table. With that, the client can decided which way to classify each FSA.

This is only one example of the types of analysis that can be done. There are also the SAC and SACType attributes that may be useful, as they indicate whether the FSA is influenced by a CMA / CA or not. Hmm, I just took a quick look at that, and that may prove more useful. I’ve included that table in the workbook as well.

Anyway, there is no easy way to classify the FSAs are rural/urban with the PCCF. The client will have to do some sort of analysis of the attributes (PopCentre or SAC or perhaps something else that makes sense to them), then make some decisions as to how they will classify each FSA.”

Wednesday, May 29, 2019

PCCF in csv Format

Until we complete hiring a new data librarian, I’m the contact for anyone in our institution needing the PCCF and PCCF+ files and my knowledge is very limited. Usually I just provide the files and all is good, but now a grad student who has received the files sent me the following: “I am not familiar with SAS. Could you please send me a csv or Excel file which contains the postal codes and corresponding regions”.

I’ve received the following response from the PCCF team:

“We do not provide the PCCF or PCFRF files in csv or Excel format. The files are quite large, and would take up even more room if they were provided is some application format. They are provided as a flat, fixed width, ASCII text file (.txt), which is readable/importable into a wide variety of applications. This is not a format specific to SAS. The client should be able to use it in whatever data application they are familiar with.

The record layout is provided in the Reference Guide (page 11 in the 2019 February version). That explains the format of the text file, and how the client needs to define the file in their application.

It’s not the most convenient way to provide the files. However, it is the format that is usable in the most applications, and has the smallest file size.”

Crime Data at Census Tract Level

A researcher is looking for crime data at the CT level for 2016 and 2011. As far as I know, data from the Uniform Crime Reporting Survey is only available at the provincial or CMA level. I have seen some CT tabulations for Montreal (2001) and Toronto (2006) but that’s all. Short of custom tabulation, is there any other source for this data?

Subject matter has responded with the following:

“The Montreal and Toronto reports in question were really one off special analytical products, outside the normal geographical scope of the UCR.  

The lowest geography that the UCR is published at is the police service boundary level, then it goes to CMA, then CANPROV.”

Tuesday, May 28, 2019

Temporary Workers in Canada - StatsCan Report

Re:  Temporary Workers in Canada over a 20 year period (was reported on on May 3rd). 

Does anyone know the source that the CBC reporter would have used for this story?  Labour Force? Labour Force Historical Review? (not up-to-date?)

The researcher wonders if the data is available at the occupational level for legal professionals.

At first I thought I was looking for a report but don't think so. I'll keep looking, just back after two weeks away (and the question came in almost the moment I left town.)

On our end, we've received the following response from subject matter:

"It's outlined is the article that the source is the Labour Force Survey. 

Tell the researcher that yes, it is possible to produce a cross-tabulation of job permanency status by occupational groups as a cost recoverable product. 

The would be a small percentage of suppression due to sample size.

When asking for professionals, he is referring to the following: 

    11 Professional occupations in business and finance
    21 Professional occupations in natural and applied sciences
    30 Professional occupations in nursing
    31 Professional occupations in health (except nursing)
    40 Professional occupations in education services
    41 Professional occupations in law and social, community and government services
    51 Professional occupations in art and culture"

Please let me know if you would be interested in pursuing a custom tabulation.

Labour Force Survey Custom Tab Questions

I have a researcher who is interested in a custom tab from the Labour Force Survey. Can you confirm that the following would be available as a custom tab?

He is looking at assessing socio-economic impacts of changes in the forest products sector – both mill closures and start-ups of new biorefinery ventures – and would like to develop a socio-economic index (or measures) that can be incorporated into Canmet ENERGY (part of Natural Resources Canada) I-BIOREF biorefinery simulation model.

Here are the specifications for the data he is interested in from the LFS. The attached excel file provides an illustration of the data output framework that he would like to see. It also includes a list of all the NAICS and NOC codes he is looking for.

  • Number of total workers (all industries)
  • Employment income (all workers/all industries)
  • Number of workers by industry – NAICS
  • Total Employment Income by industry – NAICS
  • Number of Employees by Occupation – NOC
  • Highest level of Education attainment
  • Geographic areas – the CA’s specified will be the focus of case study examinations within my research because each exhibits particular characteristics of change / rejuvenation with respect to the forest sector. The CA’s are: Corner Brook, NL; Val d’Or, QC; Thunder Bay, ON; and Prince George, BC. Additionally, it would also be very useful to obtain the data for two Census Subdivisions in Québec – La Tuque and Matagami – as these two communities exhibit forest industry change characteristics that are not readily observable elsewhere.
  • Time frame – the overall time period of focus / interest is 2000 – 2017. Monthly data is not essential – annualised or December end-of-year data would work just fine. My objective in pursuing the LFS data is to obtain more frequent tracking of changes in the communities than is achievable from the Census data.

I’ve received the following response from subject matter:

“The level of detail requested is too high for the CA geography.
The Labour force survey is not designed for this level of granularity.”  

Wednesday, May 22, 2019

PCCF Problem

A student here is using the latest edition of the PCCF, and is running into a curious problem -- she only gets results for two provinces - Newfoundland and Nova Scotia. I don't have any experience actually using the PCCF, so I'm stumped as to where the problem might be.

Any idea why this might be happening?

The PCCF team will need a little more information in order to troubleshoot:

"If we can get further information, as in any of the following…

— complete PCCF vintage
— software tool used to do the query / analysis (MS Access, SAS, etc.)
— what the query / analysis actually is
— results anticipated
— actual results"

Questions about Housing Data

An Education researcher here wants to work with data at the DA level that describes dwelling characteristics including rental costs, housing values, tenure.

While he may find suitable data through dwelling Variables in the RDC using the 2006 and 2016 Census files, and the 2011 NHS he was wondering how he may access data from the Canadian Housing Statistics Program (CHSP).

His questions on the CHSP are as follows:

  • What reference periods are available
  • If the program does not go back earlier than 2017, did another program collect comparable data?
  • Will a PUMF be produced under this program?
  • He may wish to explore a Custom Tabulation, if so would data at the DA level on the above noted dwelling characteristics (and possibly additional variables) be available?

I’ve received the following response from subject matter:

What reference periods are available
  • 2018
If the program does not go back earlier than 2017, did another program collect comparable data?
  • The Census is likely the best source.
Will a PUMF be produced under this program?
  • This is not planned.
He may wish to explore a Custom Tabulation, if so would data at the DA level on the above noted dwelling characteristics (and possibly additional variables) be available?

No, the CHSP provides data at the CSD level and above.

2001 to 2016 DA Correspondence File

A doctoral student is interested in comparing certain variables in the 2001 and 2016 census at the DA level.  They would like to standardize the DAs a certain year, preferably 2001.  There are correspondence files on the StatsCan website at for each census year relative to the previous census year for 2001 to 2016 (i.e., 2016 to 2011, 2011 to 2006, 2006 to 2001).  However, the student would like to use a correspondence file for 2016 to 2001, if it exists as one file.  Is anyone aware of such a file?  I realize the same task could likely be accomplished programmatically with the three correspondence files available, but I think for this student (and to be honest, for me) it would be easier with one file.

Alternately, is there a way to obtain data for a specific geographic region (Toronto) for the two census years aggregated to 2001 or 2016 DA levels?  For example, in Dataverse we have a semi-custom tabulation of certain census data from 1971-2011 standardized to 2016 DA geographies, but it doesn’t contain the variables the student is looking for.

It looks as if (on our end) we’d have to go the custom tabulation route. Please let me know if you would be interested in pursuing this and I will have the proper individuals get in touch with you.

Tuesday, May 21, 2019

Estimated Release of 2017 APS PUMF

I have a researcher interested in the 2017 Aboriginal Peoples Survey data. When might the PUMF be released? It’s not listed on the tentative release dates page yet. I understand if nothing specific is known at this time, but it would be helpful to know if it won’t be in 2019, for example.

The 2017 APS PUMF will not be disseminated until 2020 – the exact date hasn’t been determined yet however.

Friday, May 17, 2019

Data on transportation of goods (maritime, railways, etc.)

A student at M.Sc in Operations and logistics is searching for data on freight flows (volumes of consumers, industrial, material goods).

He’s starting point is the Port of Montreal. He’s looking for any data on where all those goods go, which mode of transportation is used and what is their final destination.

I have sent the information from the Port of Montreal, but it’s incomplete as to the origin of the products and where they are going.

I’ve found the table 23-10-0216-01, but it doesn’t offer the port of origin. I’ve also found the Canadian Freight Analysis Framework.

I’ve sent all these resources, but for my students, it’s incomplete.

Would you have any suggestions I might refer him to?

I apologize for the delay – I had a meeting with the individual responsible for creating the data files for very similar subjects in the past, and he is extremely excited about the prospect of someone looking for more!

Unfortunately what IS available wouldn’t be publicly accessible… Only accessible via the RDCs. In saying that however, the data is not currently IN the RDCs (it would need to be completed before-hand). This isn’t necessarily the answer I’m sure your student is looking for, however I’ve been given a few different resources that will hopefully help some:

For starters, please check out the following NATS website: (the Data Tables section offers quite a lot!)

I was given the table 6-3a to pass along that might be useful as well (see attached). This was not accessible for me via the website, but hopefully the student has better luck.

Finally, I am attaching the 2011 Marine Origin and Destination tables (Domestic and International). There is MORE information than just Montreal in these documents, and although they are a little outdated, hopefully they will be of some use.

At this point in time there isn’t much else that we could help with, however the team responsible for creating these resources are very motivated to develop new data and would love feedback if the student had any interest!

*Original Email included attachments*

Workplace Pension Plans WW2 and pre-WW2

I have a researcher looking for data surrounding workplace pension plans pre-WW2 and during WW2. He’s also interested in the gender share of workers in different industries and the gender share of new workers by industry, particularly during the Great Depression and WW2.

Does anyone have any suggestions?

... have you had a look at the Historical Statistics of Canada (2nd ed.)? 

That link takes you to Section D on the Labour Force that includes a set of tables which might address part of your question ("gender share of workers in different industries"). They can be downloaded in CSV format​.

Table D8-85

Work force, by industrial category and sex, census years, 1911 to 1971 (gainfully occupied 1911 to 1941, labour force 1951 to 1971)

Your researcher will want to read the accompanying notes on the site.

Tuesday, May 14, 2019


The latest version of the PCCF file (PCCF7B) is now available on the EFT. It can be found at the following location:


Monday, May 13, 2019

New Files on Statistics Canada Nesstar - CCHS 2015

We are pleased to inform you that the following (metadata) are now available on the Statistics Canada Nesstar WebView site.
  • Canadian Community Health Survey (CCHS) 2015 Nutrition
  • Canadian Community Health Survey (CCHS) 2015-2016 Annual

GSS Victimization - Territories and Geography

I have a question about microdata files available for the GSS (victimization) cycle 28, or previous. A researcher is interested in joining data from this survey with data from the Census and therefore requires more detailed geographic information than what is available with the DLI PUMF. In the PUMF, the geographic variables only 'go down' to the provincial level. The restricted dataset has many more geographic variables available, which would be better in this case.

However, the microdata files aren't consistent with their inclusion of data from the territories vs provinces. None of the DLI PUMFs contain data from the territories. The cycle 28 RDC dataset only contains variables for responses from the provinces, while the cycle 23 RDC dataset only contains responses from the territories.

Are there any microdata datasets (RDC/DLI) that contain responses from both the provinces and territories, that will have more specific geographic variables?

I’ve received the following response from subject matter:

“It is never a good idea to ‘join data’ from two different surveys, given differences in in their populations, methodologies and time frames.

In general, the GSS is only carried out in the provinces, the exception being the Victimization cycle, last completed in 2014.

As of 2019, the GSS targets a sample size of approximately 20,000 respondents. Sometimes a cycle has a higher target sample size if funding has been received for an oversample, either in the form of a geographical sample top-up (i.e., adding more units in certain geographic areas),  a targeted oversample (e.g. focussing on immigrants, youth, or another population group), or a general oversample (i.e., increasing the raw sample size). With a final sample of 20,000 respondents, basic survey estimates are usually available for the national and regional levels, and for some provinces and census metropolitan areas. Depending on the survey topic, the sample size may be sufficient to produce estimates for certain population groups such as lone parent families, certain visible minority groups or seniors.”

Friday, May 10, 2019

New Release - LFS April 2019

We are pleased to inform you that the following product is now available.

Labour Force Survey (LFS) - April 2019

This public use microdata file contains non-aggregated data for a wide variety of variables collected from the Labour Force Survey (LFS). The LFS collects monthly information on the labour market activities of Canada's working age population. This product is for users who prefer to do their own analysis by focusing on specific subgroups in the population or by cross-classifying variables that are not in our catalogued products. The Labour Force Survey estimates are based on a sample, and are therefore subject to sampling variability. Estimates for smaller geographic areas, industries, occupations or cross tabulations will have more variability. For an explanation of sampling variability of estimates, and how to use standard errors to assess this variability, consult the Data Quality section in the Guide to the Labour Force Survey.

EFT: /MAD_PUMF_FMGD_DAM/Root/3701_LFS_EPA/1976-2018/data/

Nesstar Webview: Labour Force Survey (LFS), April 2019

Canadian Survey on Disability 2017

I've had a request for information about this survey, and I see that it's listed as available in the RDC, but there is no metadata available on your Nesstar server. Any ideas as to where it might be? It has to exist, given that it's in the RDC. Failing getting access to the codebook, would it be possible to get some clarification on certain variables? Thanks much in advance!

I've just put in a request to get access to the codebook for this survey in order for me to code it into Nesstar - without knowing how large it is, I won't be able to accurately give a timeline just yet, however if you're in a rush I can send any questions you may have off to subject matter (or verify the codebook myself).

Canadian Freight Analysis Framework

One of our patrons is interested in inter-regional trade, and is currently using the Canadian Freight Analysis Framework ( I’ve checked the master spreadsheet and there doesn’t appear to be anything else available via the DLI, nor does it seem to be available via the RDD, but I thought I would check with you.

Specifically, the patron is hoping for a more disaggregated SCTGGroup, the type of commodity shipped.

I had quite a lengthy chat with one of the subject matter experts in this area and unfortunately we were not able to come up with anything that would have met this individual's needs. I sent an email earlier this morning on a similar subject that contained a few resources that may also be helpful for your researcher, but nothing containing inter-regional trade unfortunately.

Sorry we couldn't be of more help! I was told that this may be revisited in the future however (and these types of questions/interests help get the project moving!)

Canadian International Merchandise Trade Database

Is it possible to have:

  • Imports
  • by Country

*by 10 digit level, specifically for 4412319013 Plywood, mahogany from the Canadian International Merchandise Trade Database?

I’ve received the following response from subject matter:

“The request mentioned below is possible but entails more information.

We would need to know:
- The years required
- Monthly or Yearly

Other variables available for Imports are:
-          Country of Export
-          Country of Origin
-          Port of Entry/Clearance
-          Mode of Transport
-          US State of Export/Origin
-          Duty Collected
-          Freight
-          Unit of Measure
-          Quantity
-          Value
Please send the above variables to the client as well as what years they need and if its monthly/yearly.

Follow-Up Question:
Researcher replied with:

Range of Years - latest 5 complete years available;

Data: Yearly (imports of only 4412319013);

Unit of Measure - sheets of plywood (all sizes, most common measure 4'x8'/metric equivalent, all thicknesses, usually between 6mm and 18mm);

Quantity - Total number of sheets;

Value - Total $ CAN assessed and basis of value (eg, Retail Sale in Canada or other basis)

Follow-Up Answer:
I’ve received the following response from subject matter:

“I have looked into this data request and there are some issues with the requested data (please see in red),

Year: 2014-2018
HS10: 4412319013
Unit of Measure: The unit of measure  is associated with the HS code for the commodity. Please refer the client to chapter 44 of the HS classification. I took a brief look and it looks like it’s mostly identified as 6mm in thickness size, but the unit of measure for these commodities is MTK ( Square Metre )
Quantity: The quantity doesn’t focus on number of sheets, only on square metre.
Value ($CDN) "

Follow-Up Question:

Researcher would like another quote for just:
Total square meters of this marine plywood, 4412319013, imported into Canada in 2018
Quantity: square metre
Value ($CDN)

and assumes the value is wholesale, (not retail), correct ?

Follow-Up Answer:
I’ve received the following response:

“Unfortunately, I am unable to answer the clients question inquiring if the value is wholesale and not retail. If the client would like to seek further clarification on that specific subject matter, I would suggest contacting MWTD.

As for the price of a custom tabulation including the year 2018, the cost will remain [the same] (plus applicable tax).”

Thursday, May 9, 2019

Provincial Electoral District Census Profiles

I am assisting an economics student on a research question based around census profiles (that include ethnic origin and place of birth questions) around provincial electoral district boundaries. This is easily do-able for federal electoral districts –but I haven’t found a consistent methodology for provincial electoral boundaries. Some provinces have posted profiles on their own portals –not sure how consistent the methods are. Perhaps there’s a collocation of that I’m unaware of.


I have reached out to explore the researchers openness to a geospatial approach since most of the boundary files seem to be available.

We’ve had the following information passed on:

“As long as all of the PEDs are available online via open data, we could create a national or provincial files. We don’t currently have PED boundaries other than Ontario (which we have created and have permission to use for other organizations).

I checked with one of our geographers, and she provided the following additional information:

If the files are retrieved via open data portals I don’t think we would need permission to use them.  It doesn’t seem that there is a standard methodology, other than provinces aiming to have representation by population. From the quick look I took at the BC PEDs, the boundaries do not follow any SGCs. Provinces also amend and update boundaries at different times. For example, BC updated their PEDS in 2015, Manitoba in 2018.   I would need to consult with the client to find out if they wanted the most recently updated boundaries, or the boundaries used in the last provincial elections.

All that to say is yes, we can create them.  This would be a cost-recovery activity so there would be a charge for the work.”

CCHS 2015 and Applying Survey Weights

A graduate student has asked me where to find the survey weights for the CCHS 2015: Nutrition Component, Food and ingredient details.  In particular she’s interested in weighting the FIDDCON variable (Location of food consumption).  There is no survey weight variable for the ‘Food and ingredient details’ section of the CCHS on ODESI.  Variables often used for developing a sample/constructing weights were collected in the CCHS (age, gender, geography) and there is a Weights variable for the Canadian Community Health Survey, 2015-2016: Annual Component on ODESI, but age/gender/geo are not part of the ‘Food and ingredients details’ data set in which FIDDCON is included.  I don’t see a ‘key’/common variable that could connect the weights from the Annual Component dataset to the Food and ingredients details data set.  I’d appreciate any help figuring out how to obtain the survey weights for this part of the survey, or help understanding what I am missing about how survey weights are used.

Additionally, I’ve been reading through the documentation for CCHS2015 and having a hard time reconciling the various components and timelines and the numbers of respondents to each part of the survey.  If there’s someone on the list who is relatively familiar with this survey, I’d love to have a 30-minute phone chat about it, please just let me know a couple of times you’d be available this week or next.

I’ve received the following response from subject matter:

“The survey weights are found in the HS file. The researcher will need to merge the FID file with the HS file in order to apply the survey weights.”

Monday, May 6, 2019

Postsecondary Student Information System (PSIS)

The copy of the data on the EFT server for the above survey ends in 2011, but there is evidence that there is something more recent, as shown on

Having examined the available data, the researcher has the following question:
"These provide enrollments by high-level groupings of Classification of Instructional Program (CIP) codes, and what I am after are more fine grained breakdowns, potentially down to individual CIP codes.  Do you know how I would go about gaining access to that finer-grained PSIS enrollment data?"

I've received the following response from subject matter:

"Normal DLI resources for PSIS would not satisfy the request below and a custom request to the CIP-6 level would be far too large to be workable in table format.  I think microdata access is a must for this request.  I am currently investigating possibilities that lie outside the box.  Do you think that the client could qualify for and be able to access an RDC?"

I will let you know if they pass anything else along, however it looks as if the RDCs may be your best bet.

Modernization Bulletin

The April 2019 issue of the Statistics Canada Modernization Bulletin is now available on the EFT. The bulletin aims to keep you up to date on the latest Statistics Canada initiatives and transformations.  

EFT: /MAD_DLI_IDD_DAM/Root/ModernizationBulletinModernisation

Please note that we are currently working on having these accessible with an ISSN number in the near future!

Friday, May 3, 2019

Spending on Child Care Services

I’m assisting a researcher who is looking to answer “how much net out of pocket spending (pretax) do individuals by gender and by household composition spend on paid child care services?”. I have recommended the 2016 Census PUMF, but the researcher is looking for 2017 data from the Survey Household Spending if possible. It’s not feasible to wait until the fall for the SHS PUMF to come out. What would the timeline and cost be for a custom tab?

Hello, there is a new survey that was released April 10, 2019: Survey on Early Learning and Child Care Arrangements (SELCCA) that should be able to answer these questions. It is available in the RDCs and will be available in the RTRA program shortly.

This is a link to the Daily release  and to the survey information: We can let you know once it is in RTRA.

Follow-up Answer:
We can otherwise pursue a custom tab if the researcher wants it from the SHS instead.
We’ve received the following response:

“The table attached to this email includes data pertaining to the 2017 SHS by Gender for Child Care Services. Should they require more data than that which is provided here, we can certainly look into performing a custom tabulation.”

Wednesday, May 1, 2019

Survival analysis or Time-to-Event datasets

I have a graduate student wondering if there are any microdata sets from Statistics Canada that might be useful for survival analysis. The topic or focus of the data is not important, so long as the dataset would lend itself to this type of analysis. He already has datasets from hospital discharges, but is looking for others. Basically the dataset would need to contain microdata (not aggregated) and provide information on the time elapsed before an event happens. Common subjects are disease onset or death, mechanical failure of equipment, etc., but again any topic would work.

I hope I have explained this well enough to be understood (I only grasp it at a basic level myself!). Any help would be greatly appreciated.

I’ve received quite a lengthy response from subject matter that will hopefully help some:

“To clarify, by “time-to-event”, is the student looking for longitudinal data? For example, are they looking for data points regarding what happens in between two things (i.e. what happens to my health from the point when I am diagnosed with a  disease to when I die?)

To my knowledge, there are no longitudinal Health Public Use Microdata Files on any topic (deaths, disease onset, et cetera).  The National Population Health Survey (or NPHS) was longitudinal, but, by the very nature of longitudinal data, it does not lend well to PUMF analysis. As such, we only offer NPHS data for reference years 1994 – 1995, 1996 – 1997, and 1998 – 1999 and there is no longitudinal element to the PUMF. I have attached the NPHS PUMF questionnaire here in case the student might see some data points of interest. We also have PUMFs for the Canadian Community Health Survey (CCHS). These offer a greater range of reference periods – dating back to 2000 and in two-year intervals up to and including 2016. I have attached that questionnaire as well. If these options might work - we can offer the access for free.

Normally, to acquire data like this, some researchers apply for record linkages. This enables them to link one thing (hospital records) to another thing (death certificates) in order to make meaning about how the two records might work together regarding outcomes. However, this is not a dataset and requires an application, approvals, and is usually done on a record by record basis. I have attached a copy of the application form for record linkage to this message just in case, though I honestly do not think this is what would best meet the needs of the student. 

CIHI ( ) might also be able to offer some information relating to patient experiences, hospital stays, health outcomes, emergency care, et cetera.”