From: cem-bounces(a)lists.gking.harvard.edu [mailto:cem-bounces@lists.gking.harvard.edu] On Behalf Of Emina Omerovic Sent: Wednesday, 26 September 2018 11:38 AM To: cem(a)lists.gking.harvard.edu Subject: [cem] Matching for a continuous variable Hello, Using the example provided http://scholar.harvard.edu/files/gking/files/cem.pdf<http://scholar.harv… I am not sure how to approach matching for continuous scores eg. An IQ score. Using my data sample and the automated method, it appears all matches are within about 8 score points. If we wanted to define the coarsening to about within 15 points (eg within 1 SD) how could I do this? Thank you Looking forward to the reply Emina Omerovic BSc, MClAud Research Assistant Intergenerational Health Murdoch Children's Research Institute The Royal Children's Hospital, 50 Flemington Road Parkville, Victoria 3052 Australia E emina.omerovic@mcri.edu.au<mailto:emina.omerovic@mcri.edu.au> W mcri.edu.au<https://www.mcri.edu.au/> This e-mail and any attachments to it (the "Communication") are, unless otherwise stated, confidential, may contain copyright material and is for the use only of the intended recipient. If you receive the Communication in error, please notify the sender immediately by return e-mail, delete the Communication and the return e-mail, and do not read, copy, retransmit or otherwise deal with it. Any views expressed in the Communication are those of the individual sender only, unless expressly stated to be those of Murdoch Children’s Research Institute (MCRI) ABN 21 006 566 972 or any of its related entities. MCRI does not accept liability in connection with the integrity of or errors in the Communication, computer virus, data corruption, interference or delay arising from or in respect of the Communication.

Hi Stefano, So if I have a variable of continuous scores and want to match the sample based on scores within 1 sd (e.g. 15) rather than applying the cutpoints which creates categories of scores such that cem gender kbitssw5 (70 85 100 115 130), treatment (group) becomes the equivalent of recode kbitssw5 (0/70 = 1 "Well below average") (70/85 = 2 "Below average") (85/115 = 2 "Average") (115/130 = 3 "Above average") (130/200 = 3 "Well above average"), gen(kbittssw5_5cat) cem gender kbittssw5_5cat, treatment(group) Can I match based on freely changing cutpoints to maintain that 1 sd ? Eg. A participant with a score of 80 could be matched to someone with a score anywhere between 65 and 95, and not just between 70 and 85 Kind regards Emina From: stefano iacus [mailto:stefano.iacus@unimi.it] Sent: Tuesday, 2 October 2018 1:55 PM To: Emina Omerovic &lt;emina.omerovic(a)mcri.edu.au&gt; Cc: cem(a)lists.gking.harvard.edu; king-assist(a)iq.harvard.edu Subject: Re: [cem] Matching for a continuous variable Hi, if I understand correctly, you just need to specify the cutpoints argument in the cem() function like on page 10 (bottom) of the pdf document you mention. Usually the best thing to do is to write a simple reproducible example (R code + sample of data) so that we can help you to solve your problem. Best regards Stefano On 26 Sep 2018, at 04:11, Emina Omerovic <emina.omerovic@mcri.edu.au<mailto:emina.omerovic@mcri.edu.au>> wrote: From: cem-bounces@lists.gking.harvard.edu<mailto:cem-bounces@lists.gking.harvard.edu> [mailto:cem-bounces@lists.gking.harvard.edu] On Behalf Of Emina Omerovic Sent: Wednesday, 26 September 2018 11:38 AM To: cem@lists.gking.harvard.edu<mailto:cem@lists.gking.harvard.edu> Subject: [cem] Matching for a continuous variable Hello, Using the example provided http://scholar.harvard.edu/files/gking/files/cem.pdf<http://scholar.harv… I am not sure how to approach matching for continuous scores eg. An IQ score. Using my data sample and the automated method, it appears all matches are within about 8 score points. If we wanted to define the coarsening to about within 15 points (eg within 1 SD) how could I do this? Thank you Looking forward to the reply Emina Omerovic BSc, MClAud Research Assistant Intergenerational Health Murdoch Children's Research Institute The Royal Children's Hospital, 50 Flemington Road Parkville, Victoria 3052 Australia E emina.omerovic@mcri.edu.au<mailto:emina.omerovic@mcri.edu.au> W mcri.edu.au<https://www.mcri.edu.au/> This e-mail and any attachments to it (the "Communication") are, unless otherwise stated, confidential, may contain copyright material and is for the use only of the intended recipient. If you receive the Communication in error, please notify the sender immediately by return e-mail, delete the Communication and the return e-mail, and do not read, copy, retransmit or otherwise deal with it. Any views expressed in the Communication are those of the individual sender only, unless expressly stated to be those of Murdoch Children’s Research Institute (MCRI) ABN 21 006 566 972 or any of its related entities. MCRI does not accept liability in connection with the integrity of or errors in the Communication, computer virus, data corruption, interference or delay arising from or in respect of the Communication. - -- cem Mailing List, served by HUIT Send messages: cem@lists.gking.harvard.edu<mailto:cem@lists.gking.harvard.edu> [un]subscribe Options: http://lists.gking.harvard.edu/?info=cem<http://lists.gking.harvard.edu/… More information on cem: http://gking.harvard.edu/cem<http://gking.harvard.edu/cem> Cem mailing list Cem@lists.gking.harvard.edu<mailto:Cem@lists.gking.harvard.edu> To unsubscribe from this list or get other information: https://lists.gking.harvard.edu/mailman/listinfo/cem<https://lists.gking… - -- cem Mailing List, served by HUIT Send messages: cem@lists.gking.harvard.edu<mailto:cem@lists.gking.harvard.edu> [un]subscribe Options: http://lists.gking.harvard.edu/?info=cem<http://lists.gking.harvard.edu/… More information on cem: http://gking.harvard.edu/cem<http://gking.harvard.edu/cem> Cem mailing list Cem@lists.gking.harvard.edu<mailto:Cem@lists.gking.harvard.edu> To unsubscribe from this list or get other information: https://lists.gking.harvard.edu/mailman/listinfo/cem<https://lists.gking… [MailScanner Signature Unimi]

Thanks Carla, that seems to have some potential to it! From: Warneke,Carla L [mailto:cwarneke@mdanderson.org] Sent: Wednesday, 10 October 2018 9:44 AM To: Emina Omerovic &lt;emina.omerovic(a)mcri.edu.au&gt;au>; stefano iacus &lt;stefano.iacus(a)unimi.it&gt; Cc: king-assist(a)iq.harvard.edu; cem(a)lists.gking.harvard.edu Subject: RE: [cem] Matching for a continuous variable Hi Emina, I don’t know the answer to your question for cem, but are you wanting to do caliper matching? The code below selects 3 matches with caliper matching on age (matched within 15 years) and exact matching on stage. calipmatch, generate(calmatch) casevar(group) maxmatches(3) calipermatch(agei) caliperwidth(15) exactmatch (stage) Maybe the two methods can be combined? Carla From: cem-bounces@lists.gking.harvard.edu<mailto:cem-bounces@lists.gking.harvard.edu> [mailto:cem-bounces@lists.gking.harvard.edu] On Behalf Of Emina Omerovic Sent: Tuesday, October 09, 2018 5:30 PM To: stefano iacus <stefano.iacus@unimi.it<mailto:stefano.iacus@unimi.it>> Cc: king-assist@iq.harvard.edu<mailto:king-assist@iq.harvard.edu>; cem@lists.gking.harvard.edu<mailto:cem@lists.gking.harvard.edu> Subject: Re: [cem] Matching for a continuous variable Hi Stefano, So if I have a variable of continuous scores and want to match the sample based on scores within 1 sd (e.g. 15) rather than applying the cutpoints which creates categories of scores such that cem gender kbitssw5 (70 85 100 115 130), treatment (group) becomes the equivalent of recode kbitssw5 (0/70 = 1 "Well below average") (70/85 = 2 "Below average") (85/115 = 2 "Average") (115/130 = 3 "Above average") (130/200 = 3 "Well above average"), gen(kbittssw5_5cat) cem gender kbittssw5_5cat, treatment(group) Can I match based on freely changing cutpoints to maintain that 1 sd ? Eg. A participant with a score of 80 could be matched to someone with a score anywhere between 65 and 95, and not just between 70 and 85 Kind regards Emina From: stefano iacus [mailto:stefano.iacus@unimi.it] Sent: Tuesday, 2 October 2018 1:55 PM To: Emina Omerovic <emina.omerovic@mcri.edu.au<mailto:emina.omerovic@mcri.edu.au>> Cc: cem@lists.gking.harvard.edu<mailto:cem@lists.gking.harvard.edu>; king-assist@iq.harvard.edu<mailto:king-assist@iq.harvard.edu> Subject: Re: [cem] Matching for a continuous variable Hi, if I understand correctly, you just need to specify the cutpoints argument in the cem() function like on page 10 (bottom) of the pdf document you mention. Usually the best thing to do is to write a simple reproducible example (R code + sample of data) so that we can help you to solve your problem. Best regards Stefano On 26 Sep 2018, at 04:11, Emina Omerovic <emina.omerovic@mcri.edu.au<mailto:emina.omerovic@mcri.edu.au>> wrote: From: cem-bounces@lists.gking.harvard.edu<mailto:cem-bounces@lists.gking.harvard.edu> [mailto:cem-bounces@lists.gking.harvard.edu] On Behalf Of Emina Omerovic Sent: Wednesday, 26 September 2018 11:38 AM To: cem@lists.gking.harvard.edu<mailto:cem@lists.gking.harvard.edu> Subject: [cem] Matching for a continuous variable Hello, Using the example provided http://scholar.harvard.edu/files/gking/files/cem.pdf<http://scholar.harv… I am not sure how to approach matching for continuous scores eg. An IQ score. Using my data sample and the automated method, it appears all matches are within about 8 score points. If we wanted to define the coarsening to about within 15 points (eg within 1 SD) how could I do this? Thank you Looking forward to the reply Emina Omerovic BSc, MClAud Research Assistant Intergenerational Health Murdoch Children's Research Institute The Royal Children's Hospital, 50 Flemington Road Parkville, Victoria 3052 Australia E emina.omerovic@mcri.edu.au<mailto:emina.omerovic@mcri.edu.au> W mcri.edu.au<https://www.mcri.edu.au/> This e-mail and any attachments to it (the "Communication") are, unless otherwise stated, confidential, may contain copyright material and is for the use only of the intended recipient. If you receive the Communication in error, please notify the sender immediately by return e-mail, delete the Communication and the return e-mail, and do not read, copy, retransmit or otherwise deal with it. Any views expressed in the Communication are those of the individual sender only, unless expressly stated to be those of Murdoch Children’s Research Institute (MCRI) ABN 21 006 566 972 or any of its related entities. 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