“…or multiple-probe designsAlves et al (2015) 11 M = 2.10, SD = 0.09 M = 0.11, SD = 0.01Ayala et al (2013) 10 M = 1.36, SD = 0.01 M = 0.06, SD = 0.0004Barber et al (2018) 6 M = 2.27, SD = 0.16 M = 0.03, SD = 0.004 3 M = 2.26, SD = 0.02 M = 0.03, SD = 0.0003Burns et al (2015) 3 M = 2.89, SD = 0.20 M = 0.18, SD = 0.01Coulter et al (2015) 3 M = 1.57, SD = 0.02 M = 0.04, SD = 0.001Datchuk et al (2019) 8 M = 3.32, SD = 0.01 M = 0.03, SD = 0.0001 De LaPaz et al (2013) 6 M = 1.85, SD = 0.20 M = 0.19, SD = 0.02Dennis et al (2015) 12 M = 2.60, SD = 0.13 M = 0.10, SD = 0.01 12M = 1.66, SD = 0.13 M = 0.05, SD = 0.004 Doabler et al (2015) 4 M = 4.58, SD = 0.37 M = 0.08, SD = 0.01 Ennis et al (2019) 3 M = 2.56, SD = 0.02 M = 0.18, SD = 0.001 Farmer et al (2015) 21 M = 2.74, SD = 0.08 M = 0.06, SD = 0.002 Fishley et al (2012) 9 M = 2.23, SD = 0.09 M = 0.09, SD = 0.004 Flores et al (2014) 4 M = 3.89, SD = 0.10 M = 0.09, SD = 0.002 Freeman-Green et al (2015) 12 M = 1.92, SD = 0.03 M = 0.06, SD = 0.001 Grünke et al (2016) 9 M = 5.65, SD = 2.41 M = 0.35, SD = 0.08 Helman et al (2015) 3 M = 2.87, SD = 0.31 M = 0.09, SD = 0.01 Hughes et al (2019) 3 M = 2.03, SD = 0.002 M = 0.08, SD = 0.0001 Jozwik et al (2017) 9 M = 2.52, SD = 0.10 M = 0.07, SD = 0.003 Kong et al (2016) 8 M = 6.56, SD = 0.40 M = 0.33, SD = 0.02 Kong et al (2019) 18 M = 9.50, SD = 1.49 M = 0.63, SD = 0.29 Liu et al (2017) 3 M = 3.09, SD = 0.66 M = 0.13, SD = 0.001 Mancl et al (2012) 5 M = 5.19, SD = 0.26 M = 0.21, SD = 0.01 McKevett et al (2019) 6 M = 2.55, SD = 0.12 M = 0.11, SD = 0.005 Milton et al (2019) 15 M = 5.32, SD = 0.54 M = 0.12, SD = 0.01 Ness et al (2013) 3 M = 4.03, SD = 0.15 M = 0.10, SD = 0.004 Ok et al (2016) 4 M = 2.28, SD = 0.16 M = 0.06, SD = 0.004 Orosco et al (2014) 6 M = 4.25, SD = 0.42 M = 0.25, SD = 0.02 Rouse et al (2014) 2 M = 2.46, SD = 0.11 M = 0.06, SD = 0.003 Satsangi et al (2015) 3 M = 3.29, SD = 0.22 M = 0.13, SD = 0.01 Satsangi et al (2018b) 3 M = 3.26, SD = 0.19 M = 0.13, SD = 0.01 Satsangi et al (2018c) 9 M = 3.22, SD = 0.16 M = 0.12, SD = 0.01 Shen et al (2018) 6 M = 2.72, SD = 0.12 M = 0.12, SD = 0.01 Viel-Ruma et al (2010) 6 M = 5.81, SD = 0.23 M = 0.14, SD = 0.02 Wieber et al (2017) 3 M = 1.95, SD = 0.06 M = 0.10, SD = 0.003 Zhang et al (2016) 6 M = 5.00, SD = 0.73 M = 0.43, SD = 0.25 Alternating Treatments Design Billingsley et al (2018) 5 M = 4.25, SD = 0.24 M = 0.35, SD = 0.02 Monem et al (2018) 7 M = 1.49, SD = 0.003 M = 0.06, SD = 0.0001 Satsangi et al (2016) 3 M = 1.60, SD = 0.13 M = 0.04, SD = 0.003 Satsangi et al (2018a) 3 M = 1.57, SD = 0.001 M = 0.08, SD = 0.0001 Wieber et al (2017) 3 M = 1.83, SD = 0.01 M = 0.18, SD = 0.001 AB Design Barber et al (2018) 3 M = 1.31, SD = 0.11 M = 0.03, SD = 0.002 Benedek-Wood et al (2014) 12 M = 1.78, SD = 0.07 M = 0.13, SD = 0.01 Burke et al (2017) 6 M = 2.21, SD = 0.24 M = 0.25, SD = 0.03 Wade et al (2010) 3 M = 2.20, SD = 0.005 M = 0.17, SD = 0.0004 ABAB Zhang et al (2012) 4 M = 4.29, SD = 0.26 M = 0.23, SD = 0.01 Changing Criterion Design Evmenova et al (2010) 9 M = 2.33, SD = 0.20 M = 0.13, SD = 0.01 Note. Cooper et al (2020) recommend standardized x:y between 1.5 and 1.6.…”