Data from, ‘Web-based Positive Psychology Interventions: A Reexamination of Effectiveness’

My reason for posting today is primarily to spruik the Journal of Open Psychology Data, an open-access journal that publishes papers describing psychology-related data sets that have been made freely available by their creators. The journal, edited since its inception by Jelte Wicherts, began life in 2013 and is published by Ubiquity Press. If you are a research psychologist, I strongly encourage you to make your data freely available and to consider the Journal of Open Psychology Data as the place to describe it.

Today, JoOPD published a paper by Rosalind Woodworth, Benjamin Schüz, Angela O’Brien-Malone, and me, describing some of the data that Rosalind collected for her doctoral thesis. I say, “some of” because the data described in the JoOPD paper relates to Rosalind’s research report “Web-Based Positive Psychology Interventions: A Reexamination of Effectiveness“, published last year in the Journal of Clinical Psychology. Our open-access research report, “Happy Days: Positive Psychology interventions effects on affect in an N-of-1 trial“, which also grew out of Rosalind’s doctoral research, is concerned with a different set of data.

How good are the students who go to university via a TAFE

Angela O’Brien-Malone and I have just had a paper (DOI: 10.1080/02188791.2018.1423953)

published by the Asia Pacific Journal of Education in which we compare the performance of students who go to Monash University directly from Year 12 with the performance of students who enter Monash University via a college of technical and further education, commonly known in Australia as a “TAFE”. The basis of the paper is our further analysis of data originally reported by Willis and Joschko (2012).

We used quantile regression with restricted cubic splines to examine the relationship between students’ Australian Tertiary Admission Rank (ATAR), their pathway of entry to university, and their performance during first-year university. The short story from a rather long paper is that we found outstanding performance to be largely confined to students entering Monash University directly from Year 12, rather than from  a TAFE. However, we also found that for any given ATAR, TAFE-entry students were more likely to pass their first year of university than were students entering directly from Year 12. To put that statement in its more striking present-tense reverse-form, students coming to university directly from Year 12 have a greater chance of failing first-year than do TAFE-entry student entering (Monash) university from a TAFE.

Having said that, it is worth bearing in mind that the TAFE-entry students are a very special, essentially self-selected bunch. For more details, have a look at the paper!

Location of NBN fibre-to-the-node (FTTN) cabinets

nbn co lack of transparency

The national broadband network (NBN) in Australia is owned and managed by nbnco limited (ABN 86 136 533 741), a company which, although subject to the Freedom of Information Act 1982 (Cth), has shown a distinct unwillingness to release information under FOI about, well, almost anything at all. Several people have made public requests through Right To Know for information about the location of the fibre-to-the-node cabinets that mark the end-point of the NBN optic-fibre network for a majority of households in Australia. None has been successfl. See, for example, the requests by me, by Karen L, and by Rick Torre.

It occurred to me that it would be possible to build a database of all, or almost all, of the FTTN cabinets in Australia if people were willing to submit their local information to a central data base. With that in mind, I’ve been photographing and noting the location of FTTN cabinets that I see and I hope to build an online repository that combines the cabinet names, locations and photographs. I’d be interested in receiving more information from readers. Please use the comments to submit details of any cabinets you see. Be sure to include the code-word MONKEY, the name of the FTTN cabinet and its GPS or, perhaps more simply, its what3words coordinates … otherwise the comment is likely to disappear automatically into the trash.

Here are the locations of a few cabinets

Note, the latitude and longitude are derived from Google Maps, which uses WGS 84 Web Mercator as its coordinate system. If one uses The List, from the Tasmanian Government, one gets the coordinates in the GDA94 system.

Name: FTTN Cabinet 7MGT-01-03-FNO-001
Latitude: -43.03719442 (43°02’13.9″S), Longitude:147.26587929 (147°15’57.17″E)
what3words: sponsorship.trash.shrugs

Name: FTTN Cabinet 7MGT-01-11-FNO-001
Latitude: -43.02978639 (43°01’47.23″S), Longitude: 147.27215363 (147°16’19.75″E)
what3words: heckle.lifting.sneaky

Name: FTTN Cabinet 7MGT-01-02-FNO-001
Latitude: -43.02932072 (43°01’45.55″S), Longitude: 147.26216443 (147°15’43.79″E)
what3words: flooring.lightbulb.formations

Name: FTTN Cabinet 7MGT-01-01-FNO-001
Latitude: -43.02498643 (43°01’29.95S), Longitude: 147.26052694 (147°15’37.9″E)
what3words: lawnmower.mere.dozes

Name: FTTN Cabinet 7MGT-01-07-FNO-001
Latitude: -43.06694496 (43°04’1.00S), Longitude: 147.25567817 (147°15’20.44″E)
what3words: stamps.broader.playhouse

One last thing, if you look carefully at the satellite images on Google Maps, you can spot the distinctive green cabinets at each of the marked locations.

Restricted cubic splines in regression

Earlier this year, Angela O’Brien-Malone and I were working on some research that involved quantile regression using restricted cubic splines. Almost without exception, the papers that I read on cubic splines cited a paper by Stone and Koo published in 1985 in the Statistical Computing Section of the Proceedings of the American Statistical Association. Clearly, the authors of the papers that I read had better library resources than I, or perhaps they did not actually read the original paper and merely cited secondary sources! Despite contacting several libraries, I found myself completely unable to obtain a copy of the paper.

Eventually I had the idea of looking to see whether I could contact the authors and by good fortune found the email address for Charles J. Stone, Professor Emeritus of Statistics at the University of California (Berkley). By even greater fortune, Professor Stone had a copy of the paper which he kindly scanned and emailed to me. Now I, like many other readers of mathematics, like to see it beautifully typeset but in 1985 when Stone and Koo’s paper was originally published, the Statistical Computing Section of the ASA was using fonts that did the mathematics little justice. So, with Professor Stone’s permission, and as a way of saying “thank you”, I have reprintted the paper using LaTex. The images are taken directly from a scanned copy of the original.

Two versions of the paper are available for download here: For North American readers, there is a copy fitted to letter-size paper. For others, there is an A4 sized copy. The paper should be cited as:
Stone, C. J., & Koo, C.-Y. (Cha-Yong) (1985). Additive splines in statistics. Proceedings of the Statistical Computing Section, American Statistical Association 27, 45-48.

I should add that I have been very remiss in taking so long to make the paper available. I shall post an excuse at a later date …

Scoring the Values in Action Inventory of Strengths for Youth (VIA-Youth)

The Values in Action Inventory for Youth (VIA-Youth) is a 198 item self-report questionnaire that is very similar to the better known VIA Survey of Character. It was developed by Nansoon Park and Christopher Peterson who first described it, I think, in a paper [3] in the Journal of Adolescence. The VIA-Youth measures 24 so-called ‘character strengths’ [4] organized under six broad ‘virtues’ and is intended for use with young people aged 10–17 years.

The journal paper [3] explains that the authors, ‘ with different item formats and phrasings before arriving at the current inventory, which contains 198 items (7–9 items for each of the 24 strengths, placed in a nonsystematic order), about one-third of which are reverse-scored. … Respondents use a 5-point scale to indicate whether the item is “very much like me” (=5) or “not like me at all” (=1). Subscale scores are formed by averaging the relevant items.’ Unfortunately the explanation of the scoring ends there.

I had not heard of the VIA-Youth until yesterday when I was asked, by someone who had seen my earlier blog posting [2] on the VIA Survey of Character, whether I knew anything about the VIA-Youth scale. I didn’t, but found, amongst other copies, a Master of Science dissertation [1] that contains a copy of the VIA-Youth. With a knowledge of the 24 character strengths, it is not difficult to infer the scoring key.

There are some differences from the way that the adult scale is scored. Items 1–168 are in seven repeating blocks of 24 questions. Within the 24 item blocks, the Character Strengths are in the same order. However, the items from 169–198 are different. The next block would normally be from 169–192, but in fact it is from 169–191 because the item for the character-strength of “Forgiveness” has been omitted. The remaining 7 questions (192–198) are for the character strengths called Fairness, Humour, Perseverance, Kindness, Love, Humility and Self Regulation.

The other difference between the Youth scale and the adult scale is that all the adult items are scored the same way. However, as Park and Peterson commented in their paper, some of the youth items are scored in the reverse direction. I have provided links to two spreadsheets that describe the scoring key completely. The first spreadsheet is in Open Document format [ODS-link], the other in Microsoft Excel format [XLS-link]. I have indicated in the spreadsheet whether the item is scored in the + direction or the – direction. More clearly, I have indicated whether the responses should be scored 5..1 (meaning that “Very Much Like Me” is 5, and “Not Like Me At all” is 1), or 1..5 (meaning that “Very Much Like Me” is 1, and “Not Like Me At all” is 5).

I expect that having the scoring key readily available will promote greater empirical examination of the scale.


[1] Dieckman, D. (2009). Locker Room To Life: Do Sports Build Character? Dissertation for the degree of Master of Science in Guidance and Counseling. University of Wisconsin-Stout. [link]

[2] Diamond, M., O’Brien-Malone, A., & Woodworth, R. J. (2010). Scoring the VIA Survey of Character. Psychological Reports, 107(4), 833-836. DOI: 10.2466/02.07.09.PR0.107.6.833-836

[3] Park, N., & Peterson, C. (2006). Moral competence and character strengths among adolescents: The development and validation of the Values in Action Inventory of Strengths for Youth. Journal of Adolescence, 29(6), 891–909. DOI: 10.1016/j.adolescence.2006.04.011

[4] Petersen, C., & Seligman, M. (2004). Character Strengths and Virtues: A Handbook and Classification. Oxford: Oxford University Press.